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A product manager’s reflections for a better 2021

This year I tried something different. I wanted to craft an article each month on an interesting thought or lesson from my life as a product manager. It’s been a long time since a year lived has taught me so much on living and working well. In this article, I’ve summarised some of my most exciting ideas from the year. I hope you enjoy it and that it helps with your own reflections as we move forward together into 2021. 1. Turn your team into an idea factory How to Persuade a Product Manager Good ideas give us more opportunities for success. We should encourage our teams to develop their thoughts with systems that provide them with confidence in the validity of good ideas. The riskier the idea the more time you should probably spend thinking it through. If you want to check you are solving a valuable problem question ask this question — how much would you need to pay somebody not to use your product? Further Reading 2. Difficult conversations help difficult situations A product manager’s guide for difficult conversations Being confident and skilled in having a difficult conversation frees you to not only identify and work through issues before they become big problems. Further Reading 3. Build for resilience while planning for change Product strategies for after the pandemic Things not going to plan is a fact of life. The best we can do is put in place plans and mental models on how to be resilient to disruptive events biologically, psychologically and socially while also keeping an eye on any opportunities that may emerge as a result. This year it was the pandemic, next year we don’t know. But we can be mentally prepared for the worst when it emerges. Further Reading 4. Product managers don’t build products, they make decisions Decision making for product managers The creation of products is the result of a bunch of little decisions stacked together. The benefits of a series of healthy choices have the power to compound returns over time, so you really want to give yourself the best chance of making the best choices you can. By leveraging decision-making models, you can run your thoughts through a range of perspectives that help engage your thinking and hopefully work through any blind spots and biases. Further Reading 5. When luck happens all you can do is control your response Luck vs skill in determining product success Luck events, both good and bad, are out of your control, unevenly distributed and inevitable. Being at the mercy of luck puts us into a reactive mindset which usually means we don’t make the best decisions as we try to get away or lean into luck events. Pausing a second and being able to zoom out of the situation enables us to acknowledge a luck event is occurring. This the first step towards taking back control and planning for the best outcome now and later should such an event occur again. Further Reading 6. Taking notes makes you a better thinker Building a Second Brain for Productivity In product management, we highly valued for our ability to generate valuable ideas, solve challenging problems and draw strategic insights across the disciplines of sales, tech and design. So it makes sense that anything that helps us perform those tasks more effectively will be welcomed. A curated note-taking system that encourages you to think through what may be valuable from a range of sources is a significant first step to catalysing your thought process and its impact. What you are actually doing is thinking about thinking; almost a form to metacognition. Further Reading 7. Understanding user problems requires second-order thinking How product managers should understand users When people describe a pain point, it can be tempting to deal exclusively with that problem, when actually the real issue lies hidden beneath the surface. It’s the equivalent of a patient taking opioids for a painful knee when rather physiotherapy to strengthen the joint would resolve the underlying problem. For example, a user tells us their search results are not relevant, we could fiddle around with the ranking system to make it more relevant, but solving their problem actually requires a deeper understanding of their intent. We need to use a process of second-order emotional thinking to identify the most valuable problems and put ourselves in the position of the user. This enables us to image the world the way our user sees it and use the same language they use to describe it. Further Reading/Watching 8. A system for building systems makes a happy team Five product team lessons learned while building a search engine Three principles I’ve learned for fostering a healthy project team include The ability for one's mind to be changed A process of collecting feedback from teammates and users A system for developing systems when things don’t go to plan Further Reading 9. Please motivate your team, but responsibly Use motivation to inspire teams, but don’t intentionally mislead them just squeeze out some more productivity. The short term benefits may be good, but it comes at the expense of long term harm; emotionally blunting people to the pleasures of work. Further Reading/Watching

https://uxdesign.cc/a-product-managers-reflections-for-a-better-2021-8a7eb7f7887e

['Adrian H. Raudaschl']

2020-12-22 14:38:29.036000+00:00

['Product Design', 'Psychology', 'Product Management', 'UX', 'Productivity']

22 Examples of Great Copywriting in Action

Copywriting Swipe File Copywriting that addresses your customer’s concerns head-on RX bar: I love the RXbar package because it is copywriting at its simplest. It is addressing a challenge consumers face today: distrust in processed foods that have a paragraph list of ingredients. The call-out to “NO B.S.” and the simple act of listing out the ingredients immediately communicates transparency. GymIt: What is the biggest reason why someone doesn’t follow through with a purchase of your product or service? GymIt takes this answer and uses it directly in their marketing to address a top concern head-on before it becomes an excuse. Medium: While Medium no longer has this on their “Our Story” page, I really loved the call out to what they aren’t while sharing what they are. It immediately dispels any fears or hesitations about the platform that you might have been thinking about when considering signing up. Innocent: Before we can even protest or question the realness of this juice, Innocent is already letting you know that these smoothies are healthy and delicious with a fun play on words. Copywriting that makes you feel special Born Fitness: This email opt-in immediately makes you feel like you have the opportunity to join an exclusive health community. Who wouldn’t want special tips that they don’t share with anyone but their email list? We all want to feel special and in-the-know and this kind of copy leans right into that. AppSumo: With this home page copy you feel like you’ve been added to the exclusive invite list and you don’t want to miss out by passing up this opportunity. Copywriting that gives you FOMO Basecamp: No one wants to feel left out and this kind of fear, when used correctly, can be a huge motivator for trying something new or purchasing a product. Their well-timed, “Join the 4,088 businesses that signed up last week” does just that. Well if everyone else is using it, I guess I should too? Spotify: Nothing quite gives you FOMO as much as a deadline to make a decision on a discount. You wouldn’t think that stress sells, but sometimes the right amount of pressure can mean the difference between a purchase and “well, maybe later.” Campaign Monitor: This email makes you feel like you missed out, but then uses that FOMO to include you in the fun with content you can click through and dive into. Copywriting that is fun and conversational The Hustle: Sometimes all it takes for successful copywriting is a certain ease of writing that sounds like a friend is talking to you. The Hustle added in some humor, wit, and fun with their opt-in that makes the decision to let them into your inbox an easy one because they are a friend and not a sale. Metro Trains (Dumb Ways to Die): One of my favorite advertisements of all time is the “Dumb Ways to Die” public service announcement made by Metro Trains to promote railway safety. What could have easily been another boring video telling you to stay away from train tracks was creatively made into a song that still manages to get stuck in my head today. Articulate: The “About Us” page is a great opportunity to showcase your company’s personality and can benefit from some thoughtful copywriting. What I love about Articulate’s “About Us” page is that they stray away from the boring norm and in the process, they come across as fun, authentic, and trustworthy. Netflix: Sometimes the best copywriting involves little writing prowess and just timely execution. This Netflix Twitter thread makes people smile, it’s fun to retweet and share, and also simultaneously communicates what shows they have on their platform. Copywriting that knows their audience Snowbird Ski Resort: I love this creative use of a critique. By leaning into what they aren’t, they simultaneously tell you what they are and who they are for. It makes those advanced or die-hard skiers excited about coming to this mountain and experiencing the difficult slopes. Cards Against Humanity: If you know of this not-for-kids card game then you know that the use of “your dumb questions” and their sassy answers instead of the usual “Q&A” is the perfect wording for the target audience of this game. Copywriting that tells you exactly what you are going to get Sometimes it’s all about answering the question of who, what, when, and where. BarkBox: This is such a simple yet effective “how we work” section of BarkBox’s home page. It communicates what value you will receive (“spoil your pup”, “month-long dog party”, “Valued at over $40”) while also giving the necessary details (“your first box ships immediately”, “monthly dog toy”, “free shipping”, etc.). Skillshare: Instead of saying “take classes and learn new things,” Skillshare’s home page begins with this idea of curiosity and wonder. From there, once you scroll down you are invited to take a look into the platform and see exactly what a membership might offer. It’s copywriting that knows its offer and how to share it effectively. Mailchimp: Simplicity is usually best when it comes to copywriting and Mailchimp is successful at the simple explanation. “Mailchimp helps small businesses do big things, with the right tools and guidance”. BAM! Copywriting that shares your anguish or frustration This is where customer research comes into play and where you can put your business on the same side as your customer. Hey, you know that annoying thing? We hate it too. Harry’s: Instead of saying, “our razors are affordable” they are sharing a story about their business that you can relate to as a potential customer. Asana: Instead of describing what Asana is (a project management tool) they describe the end result (less busywork) while touching on a pain point many people feel at work. They even have an easy-to-understand video that accompanies their copy that provides even more detail and understanding of how it can make your life easier. Copywriting that tells a story Aubrey Marcus: So many product descriptions feel like a long list of “blah, blah, blah” and don’t spend any time inviting you in or compelling you to purchase. When a person is reading your product description they are quite literally making the decision at that moment if they want to purchase. That’s what I love about this Aubrey Marcus shoe description because it tells a story while simultaneously selling you on what kind of person wears these shoes. Everlane: Sometimes the art of telling a story doesn’t just exist in a cute advertisement, but across your entire brand. Everlane has built its brand around ethical factories and transparency in their products. Throughout their entire website, they share the story of their factories, how they make their products, where the supplies come from, etc. All of this creates a story for their brand that you believe and buy into.

https://medium.com/better-marketing/22-examples-of-great-copywriting-in-action-4c896dafa612

['Megan Elizabeth Clark']

2020-12-28 14:32:52.070000+00:00

['Writing', 'Copywriting Tips', 'Content Marketing', 'Marketing', 'Copywriting']

Who to turn to?

In the previous article, we went through the difference between emotional and academic intelligence. But one question remains; why have we not looked at this before? Surely, our ancestors also faced emotional challenges, so why has the topic remained underdeveloped for so long? Well, in most societies, the influence of religion kept emotional intelligence in a dark, unexplored corner. This isn’t to say that religion is to blame, far from it. For most of human history, religion has served as an emotional pacifier, a safe haven to run towards when things go bad. Religious leaders speak of ethical behavior, a meaning in life, community spirit, and a purpose to work towards. They show us the way to live, love, and exist in harmony with others. Even after we die, there is a promise of continuity — an afterlife. “the influence of religion kept emotional intelligence in a dark, unexplored corner.” It is for this reason that religions have (openly or subliminally) served as points of reference during times of emotional hardship. I still vividly remember my grandparents saying that during times of crisis, their first point of call all would be a priest. It was a belief shared by many, especially in fervently Christian nations. So why do we not run to a priest anymore? Why is religion no longer our go-to point? For starters, the idea that we should blindly obey a dogma doesn’t seem to fit into a world of rationale and reasoning. Today we focus on understanding how things work, rather than abandoning ourselves to the powers of a greater being. Even this article itself seeks to unravel the concept of emotional intelligence, and not merely accept it. Our individual searches for emotional wellbeing have led to the proverbial ground being pulled from underneath us. We are no longer on a level playing field but on different, separate islands each with its own set of challenges. “For most of human history, religion has served as an emotional pacifier, a safe haven to run towards when things go bad.” When things go wrong, where do we run? The answer is automatic; we gravitate towards what we have always known, to what seems familiar — to our cultures. In the absence of religion, culture fills in the gaps. We rely on our cultures, norms, values, and traditions to guide us as to what is ethically correct. How do we understand ourselves emotionally? What is our purpose? To whom do we turn to in despair? These are all questions we subconsciously pose to our cultures. “We are no longer on a level playing field but on different, separate islands each with its own set of challenges.” A Shakespearean tragedy can teach us to be wary of those around us. The Mona Lisa instructs us through an enigmatic smile. Musical compositions evoque feelings of sadness or joy. Altogether, they provide a replacement for the guidance our faiths used to offer. This isn’t to say that religion is obsolete, however, it would be a mistake to completely write off the influence of culture on our emotional beings. Just as Milan’s Duomo holds a certain atmosphere of reverence, so do the world’s prominent museums and libraries. Whether it be a greater being which we believe in or a vast accumulation of knowledge, we can’t help but feel humbled. Seeing the achievements of man or the power of a god has a profound effect. “This isn’t to say that religion is obsolete, however, it would be a mistake to completely write off the influence of culture on our emotional beings.” So what does this all mean? Will we be rushing into museums, gazing at portraits, and rationalizing our feelings in a few year's time? I doubt it. As compelling a case as culture makes, it has not replaced scripture, nor does it give us all the answers when we feel troubled. It does however serve as a reminder that we are not alone; that is some distant past, other people have felt the same way. This in itself is comforting, but not enough. Taking a step back, it seems the answer we seek was never readily available. In the past people looked to religion, today we are expected to deal with our emotions somehow or other. Although it makes no sense, we expect any moderately educated, sensible person to be able to deal with the concepts of life, death, happiness, and grief. It seems absurd that’s some of us may need guidance, however, it is the reality. The moral of the story is that although culture and religion can enable us to experience emotions such as tranquility and empathy, a deeper understanding is needed if we truly want to achieve emotional intelligence.

https://danielcaruanasmith.medium.com/who-to-turn-to-c13067f92a67

['Daniel Caruana Smith']

2020-12-22 12:58:04.124000+00:00

['Emotional Intelligence', 'Life Lessons', 'Mental Health', 'Self Improvement', 'Psychology']

Hemingway’s 3 Tips for Aspiring Writers Are Also Valid for Everybody Else

Inspiring personalities Hemingway’s 3 Tips for Aspiring Writers Are Also Valid for Everybody Else Here is why Canva Pro Image Every human being is born into this world without a manual. Everything else comes with a solid manual. Just think about all this stuff that you have. Television: A manual that describes how you should use it and what you must avoid Washing Machine: The same. The producer informs the customer what you should do with the Machine and what to avoid to ensure longevity. Mobile Phone: Pretty much the same. Please don’t throw it out the window when you are in a skyscraper on the last floor. Sound advice The human body and life? Nobody has ever written a solid manual. The only thing we get is two mentors — we call them usually parents. And that's’ it. Right after birth, we are bound to accept our parent’s truth, regardless of whether they are right or not. One of my biggest questions in life still is: How the hell should I live this life so that I am happy most of the time and go to sleep with a smile on my face — most of the days. It was tough to find answers before the internet started, and even 10 years ago, almost nothing was published that provided answers to the questions. But times got much better. Today many people post YouTube videos or write Articles on platforms like Medium with inspiring content from people who achieved success on all levels of life: Family Friends Arts Business and Health Recently I came across one of these masterpieces. I loved reading the article as it provided sound advice from one of the writers I admire the most — Ernest Hemingway. The article is based on the book With Hemingway: A Year in Key West and Cuba. Unfortunately, it is out of print, and the second-hand versions are not shipped to Austria. I can trust Tom Beck — the author of the article — that he cited accurately. The third quote is from the article “Monologue to the Maestro: A High Seas Letter,” While reading the article, one feeling grows stronger. It started with the first quote, and after reading the whole piece, I am confident that these three quotes are not only for writers but useful for everybody. So here is my interpretation of the quotes: Canva Pro Image Learn to Understand Your Emotions “Watch what happens today. If we get a fish see exactly what it is that everyone does. If you get a kick out of it while he is jumping remember back until you see exactly what the action was that gave you the emotion. Whether it was the rising of the line from the water and the way it tightened like a fiddle string until drops started from it, or the way he smashed and threw water when he jumped. Remember what the noises were and what was said. Find what gave you the emotion; what the action was that gave you the excitement. Then write it down making it clear so the reader will see it too and have the same feeling that you had.” — Ernest Hemingway Tom Beck states that good writing comes from real experience, and good writing centers on objects in the world, not abstract ideas. Ernest Hemingway’s quote is not only for writers. Matthew McConaughey makes a similar statement in his book “Greenlights.” Matthew describes his method of journaling that he practiced for more than 30 years. He recommends observing what the environment and activities cause on an emotional level. I agree with that. Whenever I go to a new bar and eat some new food, I try to figure out what happens. The next morning I write it down. Did you ever have this experience that you go out without drinking alcohol the next morning, you feel a huge hangover? The questions are: What did you do the night before? What did you eat? Whom did you talk to? What topics did you talk about? Once I sat in a bar and started talking with a stranger. For hours I heard how miserable his life was, how unfair he was treated by everybody in his life, and how miserable our society is in general. The next morning I felt simply horrible, which is in my eyes a natural result of too much negativity. Whenever I experience something, I write it down and do my best to navigate around such problems. Don’t get me wrong. I do not talk about giving up being empathetic, but human beings — especially strangers are no emotional garbage bins in which everybody can pour in their negativity at will. On the contrary, write down what feels good. Every year I try something new to find out whether it improves my life or not. By doing so, I found out that learning new things is pure joy for me and adds tremendous quality to my life. Not necessarily to master everything I learn, but getting more insights into life itself is worth the learning process. I practice guitar for years, yet I don’t think it has created a notable skill. But whenever I am worried or sad or anxious, and I pick up the guitar to practice, I feel better 5 minutes later. How I found that? By trying new things and writing down how it makes me feel. Probably not in that great detail that Ernest Hemingway referred to, but I am working on it. Canva Pro Image Try to Understand the Situation Before Judging People “Then get into somebody else’s head for a change. If I bawl you out try to figure out what I’m thinking about as well as how you feel about it. If Carlos curses Juan think what both their sides of it are. Don’t just think who is right. As a man things are as they should or shouldn’t be. As a man you know who is right and who is wrong. You have to make decisions and enforce them. As a writer you should not judge. You should understand.” — Ernest Hemingway How often are we trapped in the simplified judgemental thinking of true and false? How often are we quick in judging and labeling any behavior as right or wrong. Judy betrayed her husband with a family friend; it made her a slut and ruined the family. The poor abandoned and betrayed their husband. We hear parts of a story and come up with a definite solution thinking it is right. Ernest Hemingway describes not to do that. Life is a complex process of actions and reactions that create events that are events. We, humans, give them meaning and assign emotions to the outcome of events. Sometimes it is good to have a certain situation correctly labeled. For example, a funeral is a sad event as a beloved member of a family passed away. Everybody has somebody who loves them. Showing respect and understanding for such a sad situation is the right thing to do. And yet, in other situations, we come up quickly with a definite solution while we have not really tried to understand the situation as a whole. What about Judy? How would it be instead of being judgemental behind her back to ask her why she did it? Maybe she tells you a sad story about how her husband abused her daily, told her that she was an ugly fat cow when nobody was watching. That it would be best for her to leave the house and be gone forever. Does that make the husband a bad man? I mean, man is overly expressive in their emotions. So what might be the reason he acts that way? Maybe they lived in a time where Judy accidentally got pregnant, and out of social standards, they felt the need to marry and move in together. But on a human level never were a good fit. Maybe the part of the story Judy would never tell was that she told her husband daily that he is the sole reason for her miserable life. Wouldn’t she have conceived a child from him? She would have met a better man. Maybe it is just that they tried their best to be there for their child, but never were a perfect fit, so separation is inevitable, and by changing their life circumstances, they met people afterward that bring out the best in them. I learned not to trust the first reaction to a story and to start digging deeper and trying my best to see the entire picture before making a judgemental decision. Canva Pro Image Listen! Listen! Listen! … don’t speak. “Listen now. When people talk listen completely. Don’t be thinking what you’re going to say. Most people never listen. Nor do they observe. You should be able to go into a room and when you come out know everything that you saw there and not only that. If that room gave you any feeling you should know exactly what it was that gave you that feeling. Try that for practice. When you’re in town stand outside the theatre and see how the people differ in the way they get out of taxis or motor cars. There are a thousand ways to practice. And always think of other people.” — Ernest Hemingway Walking through life, labeling everything, and judging a person before the person has said anything. Do you notice this pattern in your own life? The white man in the new suit must be a rich millionaire coming from wealth. Probably he had a great childhood with loving parents growing up on the bright side of life without having anything to worry about. Or maybe the white man has lost everything during the corona crisis, job, savings, and family as his wife left with the kids and vanished without notice. He pulled himself together, bought a new suit with his last money, and is on the way to a job interview that hopefully works out as otherwise, he will not have enough money left to pay for his rent. Who knows. We often see another person and immediately connect the impression with past experiences trying to make sense of what we see. These experiences can also be social stories we get told via social media. We judge quickly. Ernest Hemingway points at the importance of working on perceiving reality as it is without making judgments. Listen first. Listening means when somebody says something to clear the mind and consume the other person's words. When I sit in a bar watching people, I often see people in conversations. Well, it is not really a conversation. I like talking with people, listening to what the other person says, making one or the other note — and when the person is finished phasing out a response in my mind and then starting talking. It is a prolonged process to let people speak without interrupting, thinking about a reply — which creates a moment of silence and the moment can be long — and then starting to reply. Or not saying anything at all -just listening. But in bars, one person speaks, and the other person speaks at the same time. Both tell stories from their lives, but none of them actually listens to what the other person says. When did you really listen lately to another person?

https://medium.com/illumination-curated/hemingways-3-tips-for-aspiring-writers-are-also-valid-for-everybody-else-c30d5eb38055

['Christian Soschner']

2020-12-23 11:04:15.151000+00:00

['Entrepreneurship', 'Writing', 'Self Improvement', 'Success', 'Writing Tips']

Make Your Application Essay Harvard-Ready with AI

How AI Can Make Your College Application Essay Harvard-Ready What AI says about what makes successful Harvard and Yale admissions essays work. With deadlines looming for college applications, as many as two million college applicants nationwide will spend the holiday season putting their final touches on that most important and feared aspect of the college admissions process: the college application essay. Because of COVID, the essay is more important this year than ever before. Many applicants have been unable to sit for standardized tests like the SAT, placing an even greater emphasis on grades and essays in this admissions cycle. Given my long-running interest in AI storytelling, I started with a simple question: can AI improve the college application essay? The answer is a resounding YES, and not in years or decades, but right now. You should follow this advice before submitting your application essay in the coming weeks! And I have the data to prove it. I analyzed more than 100 successful application essays that I found online. The dataset includes 55 successful Harvard application essays, 50 successful Yale admissions essays, and more than 30 “before” and 30 “after” publicly-available essays submitted by actual applicants prior to any editing or coaching and the same essay post-coaching. I ran each essay through Grammarly’s AI to compile helpful statistics and to look for commonalities. My questions included: Is there something different about successful Harvard and Yale admissions essays not shared by their less prestigious brethren? Are Harvard essays better scoring than Yale essays? Are there any actionable insights for applicants to improve their essays? Do paid essay coaches improve the score of the essays based on “before” and “after”? While I have no connection to or relationship with Grammarly, I chose the platform because it is among the leading consumer writing AIs on the market, and it’s mostly free. According to TechCrunch, that company is valued at more than $1 billion, and it has invested at least $200 million in its technology, so I figured it was worth a shot. Additionally, I chose EssayMaster as the source of essays because they have many successful essays accepted by top schools and because I advised the founding editor there, who was a long-time head of admissions at a university. My Awful Harvard Admissions Essay But, maybe, the real reason I went down this rabbit hole is that I just had to know if my application essay, the one I wrote to get into Harvard, was as perfect as I imagined it was 25 years ago. Twenty-five years ago, I submitted my essay to Harvard, and nobody but me edited it, no machine or human. I didn’t even show it to my parents, and it worked, I got in. But based on my analysis, I would not have gotten in today. My essay scored atrociously on Grammarly, with an overall score of 83. When compared to modern successful examples, it is not even in the same league. If a similar applicant with my grades and test scores submitted the same trite, poor-scoring garbage to Harvard today, that poor soul would almost certainly be denied, and, based on the data, probably even Yale wouldn’t take her. I still remember the name of my essay, and I even managed to find it: “Hiking to Understanding.” I’m afraid the essay did not improve from its cringe-worthy title, and today, I’m horrified by the adverb-laden text. After reading On Writing by Stephen King, I’ve learned to hate adverbs, although I fail to hate them enough apparently 😊. My sister whose application essay scored better than mine But, that terrible score, that 83, would be fine, so long as my sister, Catherine, who is eleven years younger than me and went to Georgetown, had a worse score. So I asked her for her essay. When I saw her proud title, “The Four Corners of Me,” I thought I had a chance. She scored a not particularly respectable 90. As it turned out, compared to modern Harvard and Yale goers we both stunk, but I stunk far worse. So now I have that to deal with at family get-togethers. Needless to say, I would never have submitted an 83, because today I would not be foolish enough not to avail myself of AI-assisted editing. In fact, I would go so far as to say that submitting an application essay without any reference to an AI is an anachronism, like gas-powered automobiles. The truth is AI can improve your admissions essay, and I will tell you how, but first, it’s important that you know this one thing about what the AI is doing: it is beyond your comprehension. As it turns out, that’s not an insult. For the purposes of the admissions essay and for this article, all you must know about deep-learning algorithms is this: the reason why the computer composes one sentence and not another or says one thing is wrong and not another is completely incomprehensible to a human seeking to deconstruct the algorithm, even in principle. That simply is the nature of machine-learning. No less an authority than Wired Magazine has observed that the nature of the technology is that it “produces outcomes based on so many different conditions being transformed by so many layers of neural networks that humans simply cannot comprehend the model the computer has built for itself.” Ok, so now that you know you can’t understand it, how can AI improve an admissions essay? Five Easy Steps to Improve Your College Application Essay with AI Here are the goods. Based on the data, you should do these 5 things to optimize your essay: 1. Score at least a 95 on Grammarly for “Overall score.” The successful Harvard and Yale essays in the data set scored an average score of 97.4 and a median score of 98. Meanwhile, the average “before” for an essay in the EssayMaster dataset is an 88.1. This is a significant difference, but should surprise no one that applicants to Harvard and Yale generally write better than the average applicant; however, the data also shows this gap can be closed. Interestingly, the average “after” score for an essay is a 97.6 — a score in-line with what a student is expected to have for Harvard or Yale admission. Wise applicants should run their essays through Grammarly, it’s free for the basic service, to see how you score and to work to improve that score. 2. All college admissions essays should score “Very Engaging.” This is an important baseline. Every single successful college admissions essay accepted by Harvard or Yale in the dataset was “very engaging” based on Grammarly’s score. You have all the time in the world to write your essay. If your essay is not scoring “Very engaging” you should consider why and see if you can improve it. Needless to say, my essay did not score at that level. My 1995-written essay was a bit bland by Grammarly’s metric, apparently, the kiss of death given every single essay in our dataset accepted by Harvard and Yale scored “very engaging.” My sister’s successful Georgetown essay, unfortunately, also achieved this bar, scoring “very engaging.” Kudos Catherine! 3. Get the delivery “Just Right” About 87% of accepted Harvard and Yale essays had a delivery that scored “Just Right,” the rest were “Slightly Off.” Though less important than being engaging, getting the delivery correct and tonally accurate is important for a successful essay. With that said, the 13% of the essays that were “slightly off” still got into Harvard and Yale. Not surprisingly, a higher proportion, nearly one-third, of the “before” essays were “slightly off.” To improve your delivery, there are free resources, like this admissions essay help course, to learn how to improve an essay’s delivery yourself. 4. Use 50–55% unique words and ~33% rare words but don’t thesaurus-ize! The percent of unique words is a measure of how many total words are in the essay just once over the total number of words. The percent of rare words is words that are less frequently used in English. The Harvard and Yale essays had an average of 54% unique words compared to the other essays’ 48%. The minimum number of unique words in the Harvard and Yale essays was 40% versus 34% for the other essays. Rare words told a similar story. The percent of rare words used in a Harvard or Yale admissions essay was 33% versus 31% for the “before” essays. But do NOT thesaurus-ize. Stephen King’s advice is more true today than ever before: “Any word you have to hunt for in a thesaurus is the wrong word. There are no exceptions to this rule.” — Stephen King If the word doesn’t come naturally to you, you could be committing a horrific error in language and make it the easiest possible “No” for an admissions officer. 5. Be at least “clear.” 66% of Harvard and Yale essays scored “very clear.” Of Harvard and Yale essays, 66% scored “Very clear” on Grammarly’s clarity metric, while 11% were “mostly clear,” and 23% were “clear.” That being said, this appears to be the least useful metric reported by Grammarly, given that a greater percentage of the “before” essays were very clear. The takeaway is this: So long as you are “clear” or better, then you are in good company. So, are Harvard essays better than Yale essays … and other urgent questions? We started this journey with a few urgent questions. Here are the answers: Successful Harvard and Yale essays score better than other applicants’ essays by about 10 points on Grammarly. They use more unique and rare words, and they have “just right” delivery. On the question of whether Harvard essays score better than Yale essays, Harvard beats Yale 98 to 98 . That is, Harvard essays are NOT better scoring than Yale essays. The medians of both were 98. Yale has slightly more unique words and Harvard slightly more rare words. . That is, Harvard essays are NOT better scoring than Yale essays. The medians of both were 98. Yale has slightly more unique words and Harvard slightly more rare words. There are some pretty obvious things applicants can do to improve their essays. Most importantly, have an overall score of at least a 95 on Grammarly, and aim for a “very engaging” score and a “just right” delivery score. Don’t sweat the clarity score, so long as it is “clear” or better. On the question of whether paid essay coaches improved essays, it was self-evident that they did, at least by the measure of Grammarly AI. The before set scored an 88 and the after set scored a 98 for the essays in the dataset. As far as the role of AI in the practice of writing, it appears we are in a goldilocks zone, prior to the ultimate ascendancy of automated storytelling, where the best writers will not only be skilled at their craft but also proficient masters of AI. I’d expect that for the next decade or two, the state-of-the-art in storytelling will consist of an AI-assisted human edit. In no more than five to ten years, computers will reliably suggest reasonable next sentences and topics for future paragraphs, and, it will end in the singularity of Deep Story AI, where human-produced writing is clearly inferior to machine-produced creativity. In a future where sophisticated machines are producing stellar admissions essays, then the only capable scorer of such nuance will be other machines. At that point, the audience for machine writing will be machine scoring. If the perception is that admissions committees operate in a star chamber today, just wait until AI renders their candidate decisions incomprehensible, even in principle. Perhaps that day has already arrived. P.S. — Grammarly scored this article an 84 with an engagement score of a bit bland. Sorry about that. I guess not much has changed in 25 years. 🤦

https://medium.com/towards-artificial-intelligence/how-ai-can-make-your-college-application-essay-harvard-ready-90f9dde79a90

['Geoff Cook']

2020-12-26 22:02:31.762000+00:00

['Machine Learning', 'Artificial Intelligence', 'College Admissions', 'Technology', 'Writing']

Bad API design — studying confusing AppsFlyer Server-to-server API

If you want to learn how not to design APIs, you can just look at the AppsFlyer’s server-to-server events API. The purpose of this API is to enable developers to send additional events about user behavior after they installed your app. Analyzing the API Okay, let’s see what we are expected to do to send en event. Documentation opens as follows: Parameters Looks simple enough — format the URL with your application id and send some events parameters as a JSON. Let’s skip to the parameters section to start coding. Well, that is already weird. Look at the screenshot above, can you already see what’s bad here? The first thing you’ll probably notice is that that some parameter names are in CamelCase , while others are in snake_case . Naming variables using different naming styles is not aesthetic and may lead to human errors. The right way would be choosing just one naming convention and sticking to it throughout the API. The second thing is that this table lacks data types. So, are all of these parameters supposed to be strings? Well, I guess they could be, but that’s not obvious at all. Always specify data types. Oh, wait, the table says that af_events_api must always be set to true , so I guess not everything is a string, since we have at least one boolean. That also leads to another question — why exactly af_events_api must be set to true all the time? What happens if I set it to false or omit it? Well, spoiler alert: the API call will return an Exception. So, why even include this parameter if it must always be true ? What is design decision led to this? I have no idea, this is ridiculous. Some of the parameters are marked as mandatory (no questions about it), some as optional (same here) and some as recommended. Now, what exactly is “recommended”? I guess it’s the same as optional? So why not just mark them as optional? I mean, if something breaks if these parameters are not set, they should be marked as “Mandatory”. If they are optional but somehow the precision of the service is enhanced when they are set, then it should be clearly stated. Anyway, since we don’t know the data types, let’s just look at the code examples. Here goes one: Wait, what? af_events_api is a string saying "true" ? Why would they stringify a boolean value? If it’s a boolean let it be a boolean. These kind of unintuitive things lead to human errors all the time. Okay, eventValue is supposed to be a JSON, but… not just a JSON, a stringified JSON! Why on Earth should it be stringified? There is no good reason for that. It’s not like a JSON dictionary cannot hold another dictionary as one of it’s parameters. It can and it should in situations like this. Again, very unintuitive. Encoding two JSONs instead of one (request body itself and eventValue ) will also have a negative impact on the speed of your app if you have to send lots of events. Okay-okay-okay, so it’s a stringified JSON. But what parameters should be in it? The API Documentation does not even describe them! From the code sample I know that there are af_revenue which is, I guess, revenue value, af_content_type which I have no idea about and af_content_id which I also have no idea about. What do they stand for? Are all of them mandatory or not? Why should I guess? This all should be described in the first table with parameters. So we scroll the documentation and find another example of code: Seems like there is also af_quantity — AppsFlyer, do you really want me to guess which parameters can be passed as eventValue ? Scrolling even further we can observe the most hilarious thing: Did you get it? AppsFlyers API is so confusing, that even the creator of this documentation managed to confuse eventValue with event_value . And, by the way, if the value is empty it should be set to either null or omitted in the request instead of setting to an empty string which just confuses things more. Then we scroll a little more and see this: Wait, you can specify the event time? Then why the parameters table didn’t specify eventTime alongside other parameters? Takeaway You’ve seen a real-life example of bad API design. Here are all the points you need to remember in order to design better APIs:

https://medium.com/swlh/bad-api-design-studying-confusing-appsflyer-server-to-server-api-3c0a2af0b991

['Alexey Strelkov']

2020-02-21 23:16:39.144000+00:00

['Design', 'API', 'Confusion', 'Development', 'Appsflyer']

The Literally Literary Weekly Update #3

One Last Note We have 27,489 followers at Literally Literary. We have approximately 200 writers. Even with these tremendous numbers, most of the submitted works get less than 20 views. Why? Algorithms. How do we combat this and support each other? Bookmark our homepage and once a day, come here and see what you missed. The only way we can be the kind of community we all want to be is to support each others’ works by reading them. Our homepage has a Top 25–30 that is updated every single day with new works published in the last month. Below that, you will find our trending works and then the latest ones that you may have missed. Be a participant and read works from amazing writers that maybe you don’t follow yet, but might want to.

https://medium.com/literally-literary/the-literally-literary-weekly-update-3-2a710eed5ce4

['Jonathan Greene']

2020-01-08 14:24:08.348000+00:00

['Poetry', 'Nonfiction', 'Ll Letters', 'Fiction', 'Writing']

Data Science, Machine Learning and the musings.

When it comes to career selection and following its pursuit, one seldom makes head or tail of it. The following articles consists a brief discussion of several questions regarding data science and machine learning which are residing in minds of many who are about embark a new career in it or are just curious about it. Let’s clear the air, and see how they are the “Sexiest jobs of 21st century” . 1. Why one should learn Data Science and Machine Learning? As per sources, about a whopping 2.5 Quintilian (2,500,000,000,000,000,000) bytes of data is produced every day, which if stacked, can be equal to 4 Eiffel Towers. Every organization in the world, uses various strategies, tools, and professionals to make sense of this huge amount of data — Big data, but there are not enough sources to convert data into useful insights nor there are skilled professionals for it. Now, when it comes to pursuing a career in data science there are various positives to this like the pay, as per Glassdoor, a data scientist earns $ 171,345/year which is approximately 163% more than the national average salary. Additionally, there is no restriction on educational background i.e. apart from computer engineers, and statisticians, professionals from mechanical, electronic, electric, and even management realms can find a job in data science. However, the data scientist role requires a lot of skill, and experience for a lucrative wage, not everyone can get it in one go. But, other positions like data analyst, business analyst, business intelligence analyst, data architect, data engineer, and many more have been here which in the future can lead up to a data scientist position. Apart from the skills required and years of experience, recruiters are now looking onto some qualities in a person like, how curious one is? how judgmental one is? how good story-teller one is?. Many leading professionals have confessed that if a candidate is curious, judgmental, and a story-teller with less coding experience, they will still select that candidate over the one having great coding skills but no interest in data. Therefore, the doors are open for people even if they posses less polished skills. As discussed before, data scientist uses ‘TOOLS’ to sieve information from the humongous data,so what are those tools? That is when Machine Learning comes into the picture. In old days, people stored data as a tally or tick marks, and an abacus was invented to analyze the same, however, this cannot be applied to the current scenario. The machine learning realm has various algorithms that extract data, collect data, and glean insights from data as well as prepare models which once created can be used for a longer time to perform the above functions. Therefore, the process is automatized. Furthermore, prospective Data Scientists can specialize in Machine Learning and become more desirable for employers. The average salary of a Machine Learning engineer in the US is $ 114,961/year as well as requires command over Math, Algebra, and Statistics (not a PhD in Maths or Statistics) with comprehensive machine learning basics. With the increment in data, the demand for data specialists has augmented. Amidst that, a 2011 McKinsey research on Big data illustrates that “the United States alone face a shortage of 140,000–190,000 people with analytical expertise”, which conveys a great opportunity to students and other professionals to follow this field. Moreover, both occupations have widespread applications in almost every field viz. healthcare organizations use data to monitor patient health charts, military forces employ them to monitor the defense army, store managers utilize the customer data to tailor discounts and many more. To conclude, data rules the future world, and learning these skills can make the world a better place collectively, and individually as they do not necessarily require expertise to enter the field. Also, using the untapped opportunities can help build a better career prospect with a high living standard. 2. Is it possible for non-technical candidates to enter into the field of Data Science & Machine Learning? If YES, how and NO, why? Parents spend a significant amount of money in technical education, expecting a bright future of their child. To be honest, it is hard to grab a good job and survive in it for employees from non-technical backgrounds and cannot use their talent in technical field. Although the stereotypes are set by the recruiters around the globe, things have taken a turn nowadays. So, YES! a non-technical person can pursue a successful career in either data science or machine learning. Even there are success stories of a plethora of IT startups owned and created by people from a non-technical background. So, we can say Sky is not the limit. How? Let’s unravel! With overwhelming information on the internet and advice from co-workers, the turmoil is guaranteed and the mind surely hits the wall. Anyway, there are numerous ways one can make it into this industry. Firstly, the MOOCs (Massive Open Online Courses) have seen significant growth since 2012 and during the pandemic, it has boosted exponentially. Many esteemed universities like Harvard, Stanford have partnered with these MOOCs, presenting state-of-the-art course modules, hands-on labs, and assignments. On top of it, many courses do not even require technical backgrounds, therefore taking online courses can help boost confidence and skills to fill the gaps. One of the best online sites to learn are Coursera, Udacity, Udemy, Swayam to name a few. Secondly and most popularly renowned source, YouTube. Although technical videos are scarce on YouTube, the trend has seen rapid growth over the last few years and the best part is they are free! Most of the online courses are paid or require fees to generate certifications but YouTube is the best source to learn at no cost. Adding to it, there are countless YouTube channels to learn about data science and machine learning like Kaggle, Data School, Crash Course, Tensorflow, and many more. Furthermore, there is one of the oldest and impeccable source to learn skills from, i.e. books. There are lots of books for absolute beginners or “dummies” viz. “Machine Learning for Dummies” by John Paul Mueller and Luca Massaron, “Introduction to Computation and Programming using Python” by John V. Guttag, “Data Science from Scratch: First principle with Python” by Joel Grus, “Algorithm in a nutshell” by George T. Heineman, Gary Police and Stanley Selkow which are available in paperback as well as e-book versions. Apart from these, applying knowledge practically is the best way to expertise in a field. One can take part in various online competitions hosted by websites: CodeChef, Google, GeeksforGeeks, and others. Taking part in such contest is an ideal attempt to figure out one’s weakness and strength which helps channel energy and focus in the right direction saving from burnout and loss of motivation. Ultimately, be part of coding communities. The bitter truth of being a technician is that learning never ends, so have to keep a learn-it-all attitude instead of know-it-all. These communities help beginners upgrade their skill set, host various technical events, help solve technical errors, increase networking and awareness about the technology. Some of the well-known ones are StackOverflow, GitHub, Reddit, Quora, and Hacker News. Even there are certain communities specifically created for women in technology. 3. What are applications of Data Science and Machine Learning in businesses? Almost every section of business: marketing, sales, feedback, service care, employ data science and machine learning to elevate business sales and opportunities. To initiate with data science, in a multitude of ways data science aids to make better decisions employing business intelligence. Formerly, business intelligence was static but data science made it more dynamic. With big data available to multi-national companies, they take the help of data scientists to analyze the data and gain knowledge for needed strategies. The gist of the process can be explained as follows: Business understanding — Understand the context and nature of the problem from the stakeholders which guides the further process. Analytic approach — Based on the type of issue stated, a descriptive, diagnostic, predictive, or prescriptive approach is followed. Data understanding & collection — The data is collected from various sources, prepared, transformed, and visualized to understand it more. Building models — The data and algorithm selected are then trained, scored, and evaluated through several iterations and finally deployed to the stakeholders. The above process is analogous for machine learning too. Many business firms use the analyzed data for understanding customer shopping patterns and easy handling during peak hours. For instance, data science assists Walmart in interpreting customer behavior that helps them to stock products in demand along with the ones for the future. Walmart has also tailored checkouts based on each stores, that is either a self-checkout or facilitated checkout. Moreover, based on shopping cart analysis, they curate discounts and offers, organize shelves and recommend products to enhance shopping experience. Due to globalization, there are customers from several parts of the globe, and handling queries and feedback of naive level disrupts the overall experience for consumers as well as service provides. Therefore, with the help of machine learning, chatbots are integrated into the systems which can handle first wave questions aiding in customer support allowing the company to solve serious problems requiring immediate attention. One of the classical machine learning applications in the commercial sector is anomaly detection that is diagnosing fraudulent transactions. This strategy is widely applied in manufacturing to intensify productivity and efficiency, reduce costs, and optimize downtime. The procedure of collecting and analyzing data is followed by installing sensors into the system. Machine learning models process this information to find anomalous entities and analyze them to prevent further issues and damage to the system environment. Similarly, these models aid in credit card fraud, medical diagnosis, cyber-security, and many others. One of the typical utilization of machine learning and data science which is now ubiquitous on websites is recommending engines. To be more precise, while browsing through Netflix, it is hard not to notice how it has designed its home page where one can see strips of shows that are in the top 10 and recommended shows based on the watching history of the user. One might wonder, how are Netflix shows always a blockbuster? Well, analyzing the data helps them sniff the success of every show even before it is released. There are diverse practices of data science and machine learning residing in almost every step of business which over time has built a stronger understanding of the market, stock prices, customer behavior, and potential threats to the same. 4. What is Deep Learning? Elucidate its sub-categories. For many years, Artificial Intelligence stirred excitement but experienced AI winter even after Machine Learning arrived. Surprisingly, Deep Learning neural networks made a breakthrough and powered through the whole AI field bringing AI spring. Deep learning is the subset of machine learning which is a part of artificial intelligence based on artificial neural networks with representational learning. In simple words, a deep learning neural network mimics the working of the human mind but not exactly. To mention a difference, an artificial neural network is static and symbolic while a biological brain in dynamic and analog. Around the 1950s, the concept of machine learning was coined by Alan Turing, a British mathematician and computer scientist, when he predicted the human brain like supercomputers will be invented and later in the mid-1960s the idea was realized when Soviet mathematicians Ivakhnenko-Lapa created compact functional neural networks. Since then a lot of discoveries have been made and deep learning networks have found a place in various fields. Remember, all deep learning algorithms are machine learning algorithms but not all machine learning algorithms are deep learning algorithms. Deep learning models are trained using considerable labeled data for high complexity problems requiring high computational power, producing accurate results. On the downside, the trained data is hard to explain and they are expensive. In deep learning, algorithms are prepared which perform classification tasks on images, texts, and sound. Deep learning is the backbone of self-driving cars, enabling them to differentiate a person and lamp-post or recognize the stop sign. Furthermore, in devices like phones, tablets, TVs, and speakers neural networks support voice command and control. The adjective “deep” signifies the use of multiple hidden layers in the network where there is an input layer, several hidden layers, and an output layer. A conventional neural network has 3–5 hidden layers but a deep network has as many as 150. Using the labeled data, they extract features without manual intervention. One of the most popular neural networks is Convolution Neural Network (CNN) which is suitable for processing 2D data such as images. Deep learning is sub-categorized based on architectures which are emphasized in the following text: Generative — They focus on pre-training a layer using an unsupervised learning approach, which is later included in the model for further training and fine-tuning. This eliminates the difficulty of training lower level architectures. Discriminative — They process and stack the output of each layer with original information. Hybrid deep learning — Hybrid deep learning models combine the working of both generative and discriminative. Additionally, deep learning tools have become an adjunct tool in the automatic medical diagnosis of several diseases like the detection of arrhythmia, breast cancer, pneumonia, and the classification of skin cancers and brain diseases. Similarly, deep learning models have aided in learning large DNA/RNA sequences and fast-track diagnosis of COVID-19 form X-rays images with the help of a special COVIDX-Net Model comprising seven CNN models. In conclusion, deep learning has generated accurate and high complexity results exceeding human thinking and has been making avant-garde revelations from the aggregated data over time. 5. What is Object Oriented Programming in Python? Described with illustrations. Object-Oriented Programming (OOP) is a programming paradigm which organizes software design around objects rather than logic or function. in general, object-oriented programming consists of objects consisting of corresponding data structures and the required procedures, thus following a bottom-up problem-solving approach. It is mainly focused on data, not procedures. An object has two characteristics: Attributes Behavior For illustration, suppose human as an object then, attributes — name, age, gender, weight behavior — walking, crying, running Python is a multi-purpose programming language that focuses on the DRY (Don’t Repeat Yourself) concept thus producing reusable code. Python follows certain object-oriented programming principles mentioned as follows: Class In general, class is a blueprint for the object which is used to make user-defined functions. For example, a class is a sketch of human with labels on it. Class creates a method, containing the behavior and properties which object created from the class can perform with its data. Let’s define a Human as a class: #Note: Always capitalize the first letter of class name. class Human: pass Here,by using the keyword “class” we prepared an empty class, “Human”. The keyword “pass” is a placeholder indicating where the rest of the code will be placed and this python code runs without any error. The class is used make instances, which is an object containing real data such as name, age or breed. Object An object is created by instantiation of class and memory is allocated to it. To instantiate an object write the name of class “human” followed by opening and closing parentheses (). Human() One can create two objects with same name but they are not equal as they represent different memory locations. Creating a class and object in python: class Human: #class attributes species = "homo sapiens" #instance attributes def __init__(self, name, age): self.name = name self.age = age #instantiating Human class monica = Human("Monica", 25) rachel = Human("Rachel", 27) #access class attributes print("Monica is a human / {}.".format(monica.__class__.species) print("Rachel is a human / {}.".format(rachel.__class__.species) #access instance attributes print("{} is {} year(s) old.".format(monica.name, monica.age) print("{} is {} year(s) old.".format(rachel.name, rachel.age) Output: Monica is a human / homo sapiens. Rachel is a human / homo sapiens. Monica is 25 year(s) old. Rachel is 25 year(s) old. In the above program, a class is created called, “Human” with its attribute “species”. Next, attributes are defined inside the “init” method of that class. Then, instances of “Human” class are created and “monica” and “rachel” are the value/references to our new objects. To access class attributes type, __class__species. Class instances are same for all the objects of the class. In the same way, to access instance attributes type, monica.name and monica.age. However, instance attributes are specific to each instance/object of the class. Methods Methods are the functions defined inside the body of the class representing the behavior of an object. Now, unlike Java, Python can have function outside the class. Define a function: def eat(self, food): return food Creating methods in Python: class Human: #class attributes species = "homo sapiens" #instance attributes def __init__(self, name, age): self.name = name self.age = age #instance methods def eat(self, food): return "{} loves {}.".format(self.name, food) def live(self, city): return "{} lives in {}.".format(self.name, city) #instantiating Human class monica = Human("Monica", 25) rachel = Human("Rachel", 27) #calling instance methods print(monica.eat("Lasagna") print(rachel.eat("Pizza") print(monica.live("New York") print(rachel.live("Newark") Output: Monica loves Lasagna. Rachel loves Pizza. Monica lives in New York. Rachel lives in Newark. In the above program, two instance methods are defined: eat() and live(). They are called instance methods as they are called on the instances of the class. Inheritance Inheritance allows a new class to use propertied of existing class without manipulating them. Thus, the new class is called derived or child class while the existing one is called base or parent class. Illustration of inheritance in python: #Base or Parent Class class Human: def __init__(self): print("I am Human") def species(self): print("Homo Sapiens") def exc(self): print("Exercises daily!") #Derived or Child Class class Monica(Human): def __init__(self): #call super() function super().__init__() print("I am Monica") def species(self): print("Human Being") def cook(self): print("Cooks lovely!") monica = Monica() monica.species() monica.exc() monica.cook() Output: I am Human I am Monica Human Being Exercises daily! Cooks lovely! In the above program, two classes are created: Human and Monica, where (Monica) child inherits functions of (Human)parent class. This is demonstrated from exc(). Again, child class modified behavior of parent in species() method which is known as Overriding. While, child class extended parent by creating a new cook() method. Finally, super() function is used inside the __init__() method to allow the running of the parent class inside the child class. Encapsulation Employing OOP in python, the access to methods and variables can be restricted, preventing data from direct modification. This is known as encapsulation. In python, we denote private attributes using underscore as the prefix.( ‘_’ or ‘__’) Illustrating encapsulation in Python: class Food: def __init__(self): self.__cost = 10 def cuisine(self): print(" Tropical -> {}".format(self.__cost) def setNewCost(self,price): self.__cost = price f = Food() f.cuisine() #change the cost f.__cost = 20 f.cuisine() #using setter function f.setNewCost(20) f.cuisine() Output: Tropical -> 10 Tropical -> 10 Tropical -> 20 In the above program, a Food class is defined and __init__() method is used to store cost of food. Even after trying to modify the cost, it did not change in 2nd line of output because python treats __cost as a private attribute. Therefore, to change the value, setter function, setNewCost() is used, taking price as parameter. Polymorphism “Poly” means many. Polymorphism allows to use a common interface for multiple data types. Suppose we need to color a shape and there are various shapes (square, circle, rectangle). Same method can be used to color all shapes via polymorphism. Illustrating polymorphism in Python: class square: def corner(self): print("Square has 4 corners") class circle: def corner(self): print("Circle has no corners") #common interface def corner_test(shape): shape.corner() #instantiate objects s = square() c = circle() #passing the objects corner_test(s) corner_test(c) Output: Square has 4 corners Circle has no corners In the above program, two classes are defined : Square and Circle, each having common corner() method. But they act as different functions. To use polymorphism, a common interface corner_test() is created that takes any object and calls the object’s corner() method. Thus, passed c and s in corner_test() function, which ran effectively.

https://medium.com/analytics-vidhya/data-science-machine-learning-and-the-musings-886844c946a2

['Ruhi Tyagi']

2020-10-15 12:47:23.189000+00:00

['Deep Learning', 'Artificial Intelligence', 'Python', 'Data Science', 'Machine Learning']

The Secret Lives of Color. My sweet husband Rob gave me a book for…

My sweet husband Rob gave me a book for Christmas that he heard about on a podcast and thought I might like. But giving a book to someone and asking them to spend time and attention and energy on it is an act of such intimacy and audacity. I’ve been married to Rob for almost 31 years and even I had a tiny internal eye roll when I saw that he had given me a book. Like, “Really — you’re going to give ME a book? Me who reads books all day long for a living? ME who reads books all night long because there are so many I want and need to read for my work and my life? ME who has books stacked everywhere in a scattered TBR file? ME who doesn’t have a spare minute?” Note that I said internal eye roll, above. You don’t stay married for 31 years without learning something about when to keep your mouth shut. I also love to give books as gifts and frequently do so to both family and friends so it’s not like I can hold a double standard in this regard. So I smiled and thanked him and dutifully asked him where he had heard about the book (99% Invisible), and then I took the book and put it in the stack and thought I might get around to looking at it one day. That day came this week and when I cracked open The Secret Lives of Colors by Kassia St Clair, I literally gasped. It is an object of incredible beauty — which in the age of e-books, means that a great many people lavished a lot of money and attention on it. Those little dots on the cover are raised and shiny — I knew that much — as well as the fact that they used very thick paper because the book is heavy. The shock was inside, where the Table of Contents was printed in every single color written about — 75 colors printed there. And there are colored bars on the edge of the pages where each color story begins in the book, forming a deep rich rainbow on the page edges. Certain page spreads are saturated with color. Before reading a word about what the book was even about, I was eagerly trying to figure out who the author was who warranted this level of detail, and what her deal was. Turns out she is a cultural historian who has been writing about the history of color for many years for publications such as The Economist, House & Garden, and Quartz, and in a long-running column for Elle Decoration. Already loving her — a cultural historian with an expertise in color?? — I turned back to the TOC to see the most gorgeous structure. I am obsessed with the way books are shaped and structured — with how the material flows, and how it was curated and edited, and what the form of the work tells us about its function. When I am working with a nonfiction client to transform the fuzzy idea that’s stuck in their head into a powerful message that can be pressed into a reader’s hands and consumed, the bulk of what I am doing is helping them think about how to contain their idea, how to define it, how to edit it, which is to say that we are in the business of structure. I could read TOCs all day long and sometimes do when doing research on behalf of a client. My favorites ones are the ones that tell you in an instant what the book is — the whole story in just one glance. A book like Michael Pollan’s Cooked does this or The Top Five Regrets of the Dying. I just love that kind of power and clarity, because it can only come from someone with deep experience wrestling with an idea. The TOC of The Secret Lives of Color is nothing more than a list of colors printed in the colors they represent. Outside of the context of the book, printed in black and white on a piece of paper, it would literally just be a meaningless list of colors. But within the context of the book, it raises so many questions — the good kind of questions you want your reader to be asking, such as “Why these colors? And what on earth could the author possibly say about so many colors that would warrant the writing of the book?” With these thoughts in mind, I turned to the introduction, where St. Claire writes: “What I have tried to do is provide something between a potted history and a character sketch for the 75 shades that have intrigued me the most. Some are artists’ colors, some are dyes, and others are almost more akin to ideas or sociocultural creations.” I didn’t even know what a potted history was when I read those words, but I could guess that it wasn’t good, wasn’t something to be desired; it sounded like plodding, or stuck. But a character sketch of a color? Yes, please, give me that. What a concept! What an imagination that came up with that idea! What a fantastic premise for a book. (And I was right — “A potted history is brief, a quick summary. Potted meat is meat, usually not of the highest quality, processed and preserved in a tin. The expression is often used in a derogatory way.” — English.stackexchange.com) Not even 300 words into the experience of this book, and I was taken in, hook, line, and sinker. Suddenly, I was holding in my hands my favorite kind of book — a book about creativity. But it’s also about fashion and art and chemistry and science and politics and geography. There is intrigue and thievery and scandal running like an electric current through the stories. It’s written in such a way that you want to dog-ear the pages, even though you would never actually dare (and I am a devoted dog-ear-er of pages!) You keep running across sentences like this: “Colors, therefore, should be understood as subjective cultural creations: you could no more meaningfully secure a precise universal definition for all the known shades than you could plot the coordinates of a dream.” I believe I have mentioned it to ten people in 3 days, and now I am sharing it with you. The term “it speaks volumes” comes to mind. It’s just one book but it contains so much within it that is worth thinking about and sharing. No one needs this book. There is no agent who said on Manuscript Wish List, “Bring me all your nonfiction books about the cultural history of color.” There is no reader who said, “What I really want is an expensive book that teaches me something about color.” But the author was nonetheless thinking of me or someone like me when she crafted her book. She was thinking about who would care, why they would care, and how she could delight them. She was probably thinking about fashion designers and graphic designers and artists and photographers, and maybe dancers and poets, and maybe scholars and other writers, and maybe book coaches. I am just so tickled that the author wrote it and that my husband was bold enough and wise enough to know that I would love it. Aren’t you dying to write a book that one day hits someone like that? I hope you are deeply engaged in it right this very moment. And I hope you don’t stop until it’s as close to your vision as you can make it.

https://medium.com/no-blank-pages/the-secret-lives-of-colors-845b606eb5d3

['Jennie Nash']

2020-02-07 03:19:15.471000+00:00

['Books And Authors', 'Inspiration', 'Writing', 'Book Recommendations', 'Books']

What I Learned from Martial Arts as a Software Engineer

What I Learned from Martial Arts as a Software Engineer Some striking similarities between Martial Arts and Software Engineering. No pun intended :) Photo by Nathan Dumlao on Unsplash As someone who sits in front of the computer as a profession, I take my health and fitness seriously. I started training Muay Thai and Brazilian Jiu-Jitsu (BJJ) about a year ago. It’s one of the best decisions I’ve made. Before that, I was doing mostly strength and cardio training for years. I got bored with the repetitive nature of such workouts, so I decided to try martial arts. I’ve been a fan of martial arts movies since I was a kid. Jackie Chan’s Drunken Master was the first “Kung Fu” movie that I watched. My father introduced me to Bruce Lee movies. My fascination with martial arts has evolved into following combat sports like Boxing and Mixed Martial Arts (MMA). I’ve also been following the Joe Rogan Podcast for years now. That has made my decision to sign up for a martial arts gym an easy one. I’ve been pondering the crossover of ideas between being a Martial Arts student and being a Software Engineer that I had to write an essay to get my thoughts out. Before I dive into what I learned from Martial Arts, let’s start with why I chose Muay Thai and BJJ, among all other options. Why Muay Thai and BJJ? I chose both martial arts because: They are proven to be effective over the years until now with the popularity of MMA. I don’t condone any form of violence. However, the engineer in me justifies that if I’m going to learn martial arts, I might as well choose the ones that I can use in any unlikely situations. They involve explosive movements. Training teaches me the martial art as a skill while serving as an intense workout. They are accessible to me logistically. My MMA gym is walkable from my workplace and a bus ride away from where I live. They are opposites. BJJ is the “gentle art”; there’s an emphasis on neutralizing the opponent. Muay Thai is the “art of the eight limbs,” which combines fists, elbows, knees, and shins to attack. They compliment each other. BJJ is for fighting on the ground, while Muay Thai is for stand-up striking. Being proficient in both Martial Arts is akin to being a Full-Stack developer. You are skilled in both front-end and back-end development; hence it allows you to build your entire application stack just like being a well-rounded Martial Artist. 10,000 kicks I fear not the man who has practiced 10,000 kicks once, but I fear the man who has practiced one kick 10,000 times. — Bruce Lee In my Muay Thai class, trainers require the students to repeat drills after stretching and warm-up. These drills are usually knee strikes or roundhouse kicks on the bag. Roundhouse kicks and knee strikes could range from 50 to 100 reps in total for each leg. The same goes for my BJJ class. We repeat the same drills, such as forward, backward rolls, and hip escapes, before practicing the techniques or grappling. The benefits of these drills are two-fold. (1) I will master the Muay Thai strikes or BJJ movements that I repeat to the point that they become second nature. Upon mastery, I won’t have to think about the exact mechanics of a roundhouse kick, like rotating my hips, using my hand to guard my face, and pivoting on my tiptoe. I tell my mind that I want to do a Muay Thai roundhouse kick, and my body will follow. (2) It conditions my body. For example, in Muay Thai, my shins adapt to the stress of hitting the bag. In my first month of Muay Thai, I always go home with bruised shins while limping. Then my body started to adapt to a point where hitting the bag doesn’t hurt as much as it used to. As a software engineer, tasks like writing code, facilitating a useful technical discussion and presenting demos follow the same principle. I have to do the same activities over and over again to become good at it. When I was new to coding, I remember that I had to flip the pages of a book to write a simple select SQL query or implement a for-loop statement. However, after doing it some time, forming a for-loop statement in my head and writing becomes second nature. What are you willing to do your “10,000 kicks” for? Continuous feedback loop Make feedback normal. Not a performance review. — Ed Batista My Muay Thai Krus and BJJ Professors are continually going around checking each student’s technique. If they spot a bad technique, they will correct it before it becomes a bad habit. In my first private session with a former Lumpinee champion, I realized that I wasn’t consistent with my techniques. My jab, cross, and hook weren’t generating as much power as possible because of my bad form. I tend to forget to pivot with my tiptoe when I do my roundhouse kick. I tend to fall into bad habits, especially when I’m gassing out; I’d unconsciously drop my hands, making my head open to attacks. Kru-Aek corrected all of these in one session. Now that I’m more aware of these bad habits, they are now stuck in my head every time I do my drills. Getting rid of bad habits and giving way to proper technique. Some students can give you valuable feedback, as well. I recently sparred with a fellow white belt who’s ten years younger than me. He dominated our sparring session. It seemed too easy for him to take my back at will and submit me with a rear-naked choke. After our sparring, I asked him for feedback, which he gladly shared. We repeated the positions as to where I have holes in my game. He showed me what I did that made it easy for him to take my back. I learned a ton from feedback alone during my classes. In my software engineering career, feedback could be in the form of a code review, document review, formal 360 feedback, Adhoc feedback, pair programming, or performance reviews. We don’t have to wait for the performance review cycle to gather feedback if we make feedback a norm. Constant and timely feedback course correct what could form a long-term bad habit. Seeking feedback has helped me become a better software engineer. Learning what areas you suck at and correcting them will bring you to the next level. When was the last time you have asked for feedback? What was the most valuable feedback you have received recently? Belt system and the software engineering ladder The belt color in Judo indicates how hard your sparring partner can throw you down — Paraphrased from a YouTube or Reddit comment. Your competence as a practitioner is the basis of the BJJ Belt System. Muay Thai does not have a belt system. However, some gyms do implement a similar approach using color-coded armbands or pra jiad [1]. Color and ranking follow a similar progression from no armband to earning one with color rankings similar to BJJ: white, blue, purple, etc. In my current gym, you have to have at least a white pra jiad (Level 2) before you can start Muay Thai sparring. A black belt in BJJ takes on average at least ten to fifteen years to achieve. With a few exceptional cases like Gordon Ryan and BJ Penn. Gordon Ryan received his black belt when he was nineteen years old. BJ Penn received his black belt in three years and four months [2]. The belt system in martial arts somehow reminds me of the Software Career Engineering Ladder. Depending on your company, you start as an Entry Level Software Engineer, progress to mid-level then to Senior Software Engineer, Staff Engineer, Principal Engineer, and Distinguished Engineer. In theory, your “competence” determines your career progression. Every company has its own set of criteria for what it takes to reach a specific level. It’s not consistent across companies. A Senior Engineer in Company A becoming an Entry Level Software Engineer when they move to Company B is not uncommon. It’s similar in martial arts. In BJJ, for example, some gyms will require you to move down to a lower ranking belt when you join them. Or some gyms could get you promoted relatively faster than if you joined other gyms. However, in martial arts, especially BJJ, instructors could put their gym’s reputation and their students at risk if they give away belt promotions to those who are not “ready.” Let’s say you have a group of BJJ black belt students from Dojo A who went out to challenge BJJ students in Dojo B. Dojo A’s black belt students somehow got beaten by Dojo B’s purple belts. Dojo A is most likely not the gym that I want to go to in this example because of the “watering down” that happens. “Watering down” is similar to software engineers’ “title inflation” in some tech companies. You get the prestige of the job title just like how you get the prestige of getting a black belt in “watered down” dojos [3]. The beauty of the BJJ belt system is that sparring sessions and competitions can test their accuracy. Similarly, they could also test an engineer’s readiness for promotion by assigning them responsibilities meant for the level they are aiming for. However, Software Engineering ladders in any organization are prone to inconsistencies, with people finding ways to shortcut their way to promotion [4], which will be harmful to their engineers’ careers in the long run. In BJJ, most of the practitioners I met, including myself, are focused on enjoying the journey. The belt promotion is not an end goal by itself. There is more focus on mastering the art. Regardless of whether it’s a BJJ belt system or Software Engineering Ladder, any form of ranking judged by humans is still flawed. Testing the individual is the best way to achieve accuracy in the system. We should strive to give promotions to those who are ready for it. Give the belt to deserving people who can carry it. Otherwise, people will underperform if we promote them prematurely. It’s a long journey. Imagine the satisfaction of achieving your blackbelt after training in BJJ consistently for more than ten years. What do you think about the career ladder that you are in? Is there anything you could do to improve it? Humility There is no losing in Jiu-Jitsu. You either win or you learn. — Carlos Gracie “Styles make fights” — I always hear this phrase from boxing analysts. It means that no matter how good a fighter is, they eventually get beaten, regardless of skill disparity. There are fighters with a no-loss record, to name some of them: Floyd Mayweather (retired) in boxing, Jon Jones (discounting the disqualification), and Khabib Nurmagomedov (retired) in MMA. However, these fighters are one-in-a-million. A combat fighter is still bound to lose a match at some point, especially if they are undefeated in the early stage of their career [5]. When I roll with a sparring partner on the mats, my goal is to either win or learn [6]. “Losing” a roll is part of the process. Rolling reminds me to be humble. No egos on the mat. No matter how much I master a submission, someone else has already figured out a way to defend it. No matter how much I have practiced my defense, someone will find a way to sweep me. The goal is to finish the class as an incrementally better grappler than before I came in. In my software engineering career, I’ve had so many “failures.” No matter how much experience you have under your belt or how much you have mastered a tech stack, the software you’ve built is not bulletproof to outages and bugs. No matter how much you’ve tried to help your team, some things are out of your control that could go wrong. No matter how good you think you are at what you’re doing, failure is inevitable. I’m not saying that we shouldn’t aim to win. My point is to take full responsibility when we lose. However, don’t get too fixated. Learn from losing, stay humble, and move on. What have you “learned” recently? A never-ending journey If you’re going to try, go all the way. Otherwise, don’t even start. — from Charles Bukowski’s Go All The Way The world of martial arts is in constant progress. Martial arts practitioners invent new techniques. I don’t have a glamorous end goal in practicing martial arts. I want to become the best martial artist that I can be in my lifetime. I don’t aspire to fight professionally or even compete at an amateur level. I’m happy to regularly go to my gym, learn new techniques, have fun sparring, polish my game, and go home a happy man. It’s something that I look forward to every time I schedule my class. There is always something new to learn in every class; it’s either a new defensive technique, a new Muay Thai combo, or a new BJJ submission. I see myself practicing martial arts until I’m able to. The world of software engineering is in constant progress. New software tools get introduced regularly. Open-source developers build new libraries to help software engineers become more efficient in writing software. I need to get better at my craft continuously. Like martial arts, I don’t have a glamorous end goal in my career as a software engineer other than becoming the best software craftsman that I can be. I always look forward to my day job as a software engineer. There is still something new to learn every day. I see myself writing code until I’m able to. What’s your never-ending journey? Staying true to the art In closing, I will share an excerpt from the poem translated from Russian: My Sister — Life by Boris Pasternak. This poem reminds me of how I feel about practicing Martial Arts and being a Software Engineer. And never for a single moment Betray your credo or pretend, But be alive — only this matters - Alive and burning to the end. I got to know about this poem from the Joe Rogan Podcast Episode with Lex Fridman. To quote Lex Fridman’s interpretation, which I think perfectly hit it home [7]: Fame, recognition, money; none of that matters. The winning and losing; none of that matters. What matters is the purity of the art. Just giving yourself completely over to the art. Others will write your story, others will tell whether you did good or bad. Others will inspire using your story. But as the artist, you should think about the art, the purity of it and the love of it… References

https://wickedmanok.medium.com/what-i-learned-from-martial-arts-as-a-software-engineer-86cf055c4918

['Ardy Dedase']

2020-12-30 21:08:30.897000+00:00

['Life Lessons', 'Programming', 'Startup', 'Self Improvement', 'Productivity']

Listening Out For The Australian Powerful Owl

From studying law like a hawk to studying owls for science — QUT research student Callan Alexander is working with BirdLife Australia to help track and monitor Australia’s threatened powerful owl. As part of his masters research, Alexander will develop an automated species recogniser — a computer algorithm that detects a species’ call from an audio recording. To do this, he visited several nature reserves around Queensland and captured audio from the environment using acoustic monitors. “We can take audio from an area and run it through the algorithm which should tell us if there are any powerful owls around,” Alexander said. “This will help us accurately track the distribution of Australia’s largest owl, especially in remote areas that are difficult to visit regularly.”

https://medium.com/thelabs/listening-out-for-the-australian-powerful-owl-8bf729f4b759

['The Labs']

2020-12-02 23:25:50.007000+00:00

['Powerful Owl', 'Ecology', 'Environment', 'Science', 'Birds']

This Is Why You Keep Sabotaging Your Consistency

How to transform your saboteurs into allies There are so many different avenues to transforming your saboteurs into allies, so I’ll just give you the framework that is working for me. Also worth noting: These steps can happen in succession or all at the same time. Inner processes don’t usually follow a linear progression so feel free to flow in and out of these steps based on what works for you. Lastly: The book recommendations in this section are all affiliated links. Step 1: Learn the most helpful framework for dealing with your parts in general. The Internal Family Systems modality has taught me everything I need to know about the inner physics of transforming my parts. You can check out the article I wrote on it here: But I strongly encourage you to listen to Greater Than The Sum Of Our Parts by Dr. Richard Schwartz. It is honestly the most life-changing book I’ve ever read because it revolutionized my relationship with myself as well as boosted my self-awareness. I would not be able to write this article if it wasn’t for this book. Learning the IFS framework is a must if you want to successfully — and permanently — unburden and transform your parts. Step 2: Identify your saboteurs. Shirzad Chaimne has pioneered a groundbreaking system of identifying and weakening saboteurs through his Positive Intelligence program that combines positive psychology, neuroscience, cognitive psychology, and performance science. There is a free saboteur assessment on his website that I highly recommend taking. You have to enter your email to get the results, but the results are so worth it. You’ll get a detailed description of the saboteurs at play in your inner-war which will help you start a relationship with them. Check out the free Positive Intelligence saboteur test here: The only thing I don’t find helpful about the Positive Intelligence program is that it paints your saboteurs as “bad parts,” putting you at war with your saboteurs instead of in a relationship with them. The problem with this is that it offers no hope for your saboteurs to be redeemed by going back to their naturally helpful role, which limits you from experiencing true internal synergy and sets you up to war against a part of yourself for the rest of your life. However, there are so many wonderful teachings of the Positive Intelligence framework that I absolutely recommend taking the course (which I am in the middle of right now and can honestly say it is incredibly transformative) or at least reading his book, Positive Intelligence. Step 3: Cultivate a compassionate inner environment. Creating a compassionate and safe inner environment is the biggest thing that will convince your saboteurs that they don’t have to work so hard to protect you anymore because self-compassion is inherently self-protecting and self-soothing. This is why I say compassion is the great un-twister of all that has been twisted. This especially goes for self-compassion. When we are compassionate to ourselves we become strong and flexible enough weather the storms of life. We can bend, but not break. We might need a breather, but we don’t give up. We move between play and rest instead of pushing ourselves too hard and burnout. A compassionate mind is a thriving mind. And a thriving mind breeds fulfilling consistency. We were never taught self-compassion or how to be our own best friends. We were taught the opposite, actually, hence our saboteurs. We must teach ourselves how to be more compassionate, and we do this by consuming content that is not the voice of our saboteurs. I recommend reading books like the seriously transformative Self-Compassion by Kristen Neff or Learning to Love Yourself by Gay Hendricks (paid links). The book I mentioned in Step 1, Greater Than The Sum Of Our Parts also promotes a more compassionate inner-environment. If you’re tight on money or don’t read books, I suggest finding some podcasts that help people improve their relationship with themselves. I know Brené Brown’s podcast, Unlocking Us, has definitely helped me be more compassionate to myself and others. If you have your own go-to inner work podcast(s) or free resources, please post them in the comments for myself others to explore. The last thing I want to offer about creating a more compassionate inner environment is to foster a mindfulness practice or, for the more secularly oriented, practice what the Positive Intelligence framework calls “PQ reps” which are 10-second exercises you can do throughout the day. Jon Kabat-Zinn, Tara Brach, and Dan Siegel are all great mindfulness teachers. You can check out the “PQ Gym” section of the Positive Intelligence’s Resources page for more information on PQ reps. The reason meditation, mindfulness, and PQ reps are helpful in transforming your saboteurs into your allies is that they help slow your mind down enough to become aware of the conversations that are actually going on in there. Furthermore, when you are hi-jacked by a saboteur, the practice of mindfulness is the command-switch that helps your brain switch over to a more compassionate and curious environment. Step 4: Transform your saboteurs into allies. This is the part where you begin having conversations with your saboteurs. I know these parts are scary and frustrating, but it is important to begin these inner-dialogues with compassion. Otherwise, you’ll just be perpetuating your inner war and never get anywhere. Build a relationship with your saboteurs by getting curious about their stories. Some great questions you can ask them are: What is your current role? What are you trying to do for me? Why did you have to twist into this role? How did you have to twist? What are you afraid will happen if you don’t play this role any longer? If it was safe to thrive and you didn’t have to work so hard to protect our little kid anymore, what role would you rather play? Do they realize that their current role is hurting your inner child more than it is helping it? When you can get to the point of having compassion for your saboteurs and their story, you know you’re ready to begin the work of transformation. Many saboteurs will tell you they are tired of their current role, especially once they see they are hurting more than helping, but that they don’t know or can’t remember how to do anything else. Let them know this is totally normal and you don’t expect them to change all at once. Transforming saboteurs is a dance between their commitment to changing their harmful habits little by little as well as your commitment to creating a more compassionate inner environment little by little. Over time, your saboteur will realize it is safe to be vulnerable in your compassionate mind so it will take more risks through changing its habits, which will only create a more compassionate environment — creating a positive cycle. This is the consistency before the consistency. I encourage you to check in with your saboteurs (and all your parts, really) every day. Just see how it’s going. This is how you start building a compassionate relationship with yourself. One that honors all parts of you. One that fosters consistency. I am a writer so I usually check in with my parts through journaling, but even just taking a few minutes each day to touch base and see what’s going on inside of you is enough to build positive momentum. Okay — last thing about transforming your saboteurs into allies. Our saboteurs are protecting us from experiencing our wounds. They will keep protecting us from those wounds until they are healed. Permanently healing those wounds is what IFS practitioners call “unburdening.” When our wounds are unburdened, there is nothing for our saboteurs to protect, so therefore they are freed up to untwist and go back to playing a role that helps us thrive. Unburdening and healing our wounds is a deep process, though. One that takes time and usually someone to help guide us. This is why I recommend getting a therapist or coach to help guide you on your journey of inner transformation. The more IFS-oriented your therapist or coach, the better.

https://medium.com/real-1-0/this-is-why-you-keep-sabotaging-your-consistency-f4e4594da1ea

['Jordin James']

2020-10-31 00:47:31.538000+00:00

['Advice', 'Mental Health', 'Self Improvement', 'Self', 'Psychology']

5 Ways How Writing Can Recharge Your Soul

We Write Most of us write to some degree at varying stages of our lives. From early childhood scribbles, throughout our academic journey before applying our evolving skills in our chosen profession or as a hobby. Writing is a tool that humankind uses to communicate, educate, learn and create. The vast majority of us write as a function, a task relevant to our stage in life. At university, we write to study or prepare a paper. At work, we do so to compile a report, draft an email or just make notes. For some, it's simply a pastime, for others, a profession. This piece is not about the function of writing. Rather it's about the flow of writing from the soul with tips to nurture the inner passion that every writer knows, sometimes motionless and still, with periodic eruptions of creative bliss. Writing can recharge our soul when we adopt 5 simple rules for creativity. Rule №1 — Capture and record your ideas We all have plenty of ideas every single day. Think about it, how often do you have ideas? From experience, we have them much more often than we think. Ideas are born out of fleeting thoughts that blindside us on a random Tuesday. A lot of my ideas are terrible, at least initially. Then at random moments, another idea springs to mind, making a terrible idea that more appealing. In the past, my ideas were forgotten, swept away by the wind of my mind. I dismissed them without a second thought. The reality is that my subconscious mind was trying to tell me something. That's the nature of ideas, they arrive without warning. They have a tendency to crop up when we least expect it. This creative-inconvenience is something that most great writers are prepared for. They’ve learned to capture these intuitive gifts as soon as they appear. “Art is when you hear a knocking from your soul — and you answer.” — Terri Guillemets Today I record my ideas, using one of the five tools below depending on when and where an idea manifests: How to apply — There’s an abundance of choices out there for writers to harvest the fruits of our wonderful minds, so here are 5: A notepad — Good old pen and paper is one of the best ways to capture our ideas. It’s easy to do plus you never lose battery power. In the digital age, there’s something magical about writing notes on paper, igniting kinetic energy of mind and body An App — Recording notes on your smartphone is convenient when you can’t or don’t want to look for a pen and paper. There are loads of apps out there, so pick your favourite. I’d recommend Evernote or the notes app installed for free on your phone Voice — Use your phone voice recorder, or a dictaphone to speak your ideas out loud Phone — The free notes app installed on your phone is an alternative to Apps like Onenote or Evernote Share — If you’re in the company of others, sharing your thoughts at the moment they arrive is a great way to refine your idea Rule №2 — Self-expression Writing is an art form, an expression of self. It's a magical channel at our fingertips. Self-expression is the act of giving life to our thoughts, ideas and emotions. Writing funnels our ideas and feelings for deeper exploration through articles, abstract prose, poetry or personal notes. Writing is a great way to delve into the inner workings of our mind, supported by our body and soul. “I write entirely to find out what I’m thinking, what I’m looking at, what I see and what it means. What I want and what I fear.” ― Joan Didion How to apply — Never hold back. Any piece that you write is self-expressive. If you write to share with others remember to edit, cleaning out the fluff for publication. If your expression is private, write anyway, you can always delete, bin it or burn it afterwards. Have the courage to let your truthful words flow from the heart. Being open and free to express yourself by writing is a cathartic experience, a very healthy endeavour indeed. Rule №3 — Creative flow Creativity can ebb and flow. When creativity flows it’s like a river as inspiring ideas come rushing in wave after wave. Our energetic peak is prolonged as we stay awake into the early hours of the morning under the spell of deep thought. It’s a magical feeling. Then without warning — Bam — we crash. The magic vanishes. What just happened? Even our desire, our enthusiasm to write no longer burns inside. Tiny efforts to reignite that spark feels like “trying to solve an algebra equation by chewing bubblegum.” A sense of loss consumes us as we question our creative ability. Maybe I’ll never have another great idea ever again? How to apply — Chill out. This is the ebb of creativity, so perfectly normal, I assure you. No one feels the flow of creativity all the time. Like anything in life, creativity is no different than a boat on the high seas, navigating a succession of waves with plenty of ups and downs. Accept that you can never feel inspired all the time. Likewise, a crash won't last forever either. So rather than resisting the loss of that high, by trying to force it to happen again while you fret over the impending crash, stop, relax, and breath to let your flow unfurl. Learn to embrace the lows of your creative ebb today to surf the flow of ambiguity tomorrow. A constant high is a one way street to burnout. So learn to take a break. Use this time to recharge for the next wave of flow that will arrive. Downtime is a necessity for writers to nourish the soul. So be kind to yourself when you’re in an ebb-state, let the momentum unfold naturally. Rule №4 — Write from the heart to open your mind We all write articles that are … how do I put this? … dull. Uninspiring. Boring even. Devoid of personality. Pieces that lack spirit. There's no need to panic. Every writer is guilty of this. I do it all the time. It can take years to perfect a writing style that connects consistently with our readers. I’m still learning how to make my writing more engaging. Writing is a never-ending journey of discovery as we learn new ways of expressing our creative ideas. Few writers are the ‘finished article’. It’s an ongoing process, so be patient. To fine-tune your writing skill you need to be comfortable with the uncomfortable ebbs and flows of creativity. “Find a subject you care about and which you in your heart feel others should care about. It is this genuine caring, not your games with language, which will be the most compelling and seductive element in your style.” — Stephen King How to apply — It takes work to master the ability to create heartfelt and meaningful writing. It takes commitment to your art. Like any mastery, such as musicians or athletes, it can take years to develop world-class skills. So invest time in your writing. Every writer has the ability to improve their emotive expression. What I’ve learned from other writers is that there are 3 laws to this, sub-rules that enhance our ability to create inspirational writings. Here they are: Write with passion from the heart Make sure it’s relevant to your target audience Convey emotion through your words using emotive-words It’s no secret that writing from the heart opens the doorway to our soul. So listen to your heart. №5 — Connect the dots As we know creativity does not announce itself at predefined moments. It never-ever books an appointment. It only makes itself known through random ideas that spring out of nowhere. To harness the creative potential that random ideas hold, writers learn to apply two types of thinking: Convergent thinking— This is the ability to combine multiple thoughts, often very different ideas that we connect in our minds to form something completely unique. Divergent thinking — This involves cultivating multiple ideas to form a selection of potential solutions for a single idea. “Creativity is just connecting things. When you ask creative people how they did something, they feel a little guilty because they didn’t really do it, they just saw something. It seemed obvious to them after a while.” — Steve Jobs How to apply — Writing is word-innovation. A potential invention that’s incubated in the soul. Some of what we write can be dull, but over time we can learn to apply ways of thinking to raise our game and deliver a piece of work that evokes abstract thought in our readers. The best way to do this is to keep writing, even when you’re in the midst of an ebb. As Steve Jobs said, “Creativity is just connecting things”, connecting the dots to form something new or unique to share with the world.

https://medium.com/illumination-curated/5-ways-how-writing-can-recharge-your-soul-a70420aa11b2

['Paul Myers Mba']

2020-12-11 15:29:32.392000+00:00

['Writing Life', 'Entrepreneurship', 'Writing', 'Self Improvement', 'Writing Tips']

De-Mystifying Self-Motivation: How do you Develop It?

Self-Motivation: Motivated to do or achieve something because of one’s own enthusiasm or interest, without needing pressure from others. External pressure plays a significant role in helping us attain our goals. When we have a boss demanding results or a client asking us to turn in a project, producing results is a given. But what happens when you’re just starting out and you have no external pressure pushing you towards achieving a result? What happens when you are the leader, and are accountable to no one? That’s where self-motivation comes in. Imagine running a 2Km circuit after months of binge watching Netflix. Your muscles are weak, your lungs are not very strong, and your heart cannot sustain intense movements. You can feel your thighs burn as your breathing starts getting static and heavy. What seemed like a simple enough endeavour now seems impossible. Your health is in no imminent danger, so there’s no external pressure. How in the hell are you going to finish the run? Is it fine if you stop partway? After all, you’ve come a long way from sitting on your couch; it’s the effort that counts. So what do you do? Do you stop or do you finish? The answer to this question depends on your ability to self-motivate. Now, let me be clear: 1. You should not be attempting a 2Km run after months of inactivity, 2. Failing to self-motivate on one occasion does not mean inability to self-motivate on others. But a pattern of letting things figure themselves out as opposed to fighting for your goals, is a recipe for disaster. It is imperative for you to discipline yourself up to a point where self-motivation is natural…a reflex. As an entrepreneur, freelancer, or any other type of professional, your success is heavily dependent on the consistent effort you put into your work, regardless of whether or not you see results. This effort is driven by self-motivation. So how exactly do you develop self-motivation if you are not born with the trait? Well, to place internal pressures on yourself, you will need to set strict but achievable goals and outline the steps you need to take in order to meet them. Create a disciplined routine that involves you carrying out predetermined steps in a predetermined amount of time. Eventually this routine will transform from a chore you must do to an activity that you enjoy doing. Self-motivation and discipline are intertwined. A disciplined person has the ability to set internal pressure upon themselves and respond to it. This is self-motivation. Once you’ve developed the habit of running 2Km every morning, motivating yourself to increase your circuit to 3Km should not be a problem. The same thing applies to entrepreneurship. If you have the discipline to engage with 5 new organizations every day, it won’t be a stretch to motivate yourself to pitch to 5 organizations daily. If you get into the habit of writing for 20 minutes each day, motivating yourself to churn out several pieces of well-written content on a weekly basis should be simple enough. Discipline reinforces your self-motivation and allows you to pursue goals that seem out of reach for most people. If you’re serious about attaining XYZ out of life, self-motivation is key. Position yourself to develop this trait. xxxxxx Written and published by Davina Ngei — Moderator on Strategic Social Networking. Many thanks for reading, and be sure to check out Strategic Social Networking Community on Google+ to connect with tens of thousands of IT professionals online. You’re also welcome to follow Strategic’s brand page on G+ for the latest industry news. NOTE: Strategic Social Networking is Funded by The Public! Consider supporting our work on Patreon:

https://medium.com/strategic-social-news-wire/de-mystifying-self-motivation-how-do-you-develop-it-ee8423a2242

['Davina Ngei']

2018-02-07 09:10:29.611000+00:00

['Motivation', 'Entrepreneurship', 'Discipline', 'Self Employed']

5 (More) Reasons Why You Should be Writing for Medium

I’ve been writing for Medium for 2 1/2 years, and I’ve loved every minute of it! Even my worst days on Medium are fun. I love writing about writing, love engaging with other writers in this incredible community. I’m always thrilled by something every day, and every week and month is like a whole new adventure. In August I talked about five reasons you should be writing for Medium… And those, of course, are all valid reasons! It’s so much fun to write about what you want, and to actually make some income while doing it. Taking chances on new topics is fun too, as is engaging with other writers on here. And of course it’s nice once in awhile to have your writing published, rather than have it linger for years and years like so many manuscripts you might write as a novelist (I’m shining a mirror on myself with that one). Here are five more reasons to write for this site sooner rather than later!

https://medium.com/the-partnered-pen/5-more-reasons-why-you-should-be-writing-for-medium-d6bf29f9a101

['Brian Rowe']

2020-09-25 12:03:01.774000+00:00

['Writing', 'Medium', 'Success', 'Entrepreneurship', 'Love']

Let’s build an eCommerce platform from scratch

Ecommerce is the most widespread & most demanding business these days. The easiest way to buy and sell goods nowadays is mostly done online through an eCommerce platform. It is a never-ending viral loop of a quickly growing platform to provide the physical product available to an end-user or another business entity. You all be familiar with shopping online from Amazon, Flipkart, Myntra, eBay, Ali Express and many others, the working methodologies are the same as they make sure to deliver the product and build trust amongst us. Most of the businesses these days are making there own small or medium scale eCommerce platforms to reach out to more people. TL: DR; I am talking about the technical part of building an eCommerce website and app. Before you develop one, you must dive deep inside to understand the business patterns of eCommerce. For taking the next step towards developing your brand and creating your digital business platform, you need to know about your business. A little time is required to establish an eCommerce business if you have a solid understanding of your brand, trade, or idea. Brief Knowledge about your business. Designing and Prototypes Developing Testing Launching Designing Designing is all about shaping the ideas to get quality designs out of it. The artboard and web pages are designed in software such as Adobe XD, Sketch for finalizing the prototype. Creating a Database design is an essential part of designing, and we can preferably be understanding the User Flows and ER diagrams for that. You can use FlowMapp or Creately for this purpose. The collab feature in the app helps the UI team to develop the user flows much faster.

https://medium.com/phppoets/lets-build-an-ecommerce-platform-from-scratch-81a5a8a41be7

['Jay Patel']

2020-01-22 05:17:40.569000+00:00

['Design', 'Application', 'Website', 'Development', 'Ecommerce']

How I Earned $424.45 As a Side Hustle In My Free Time.

I started asking questions on Quora You can earn by writing questions on Quora. Quora pays you not for writing but for asking questions. Isn’t it sound weird! It’s their business model. It’s always hard to discover what Silicon Valley leaders think. You can earn a good amount on Quora by asking questions. For that, Quora must invite you to join a partner program. Screenshot from Author After joining the partner program, I asked around 12000 questions and earned 380 dollars in 6 months. My earning in initial months were far less than now what I’m earning. I am sharing it month wise. May- $9.23 June-$17.56 August-$22.67 September-$81.89 October- $73.78 November-$120.09 Quora partner program works like the compounding effect, where you earn after working hard for months. Quora’s earning depends on SEO, in which is your questions is ranking on googles front page you will earn more. You must know about SEO. Quora has a higher domain authority of 95. Your question gets rank quickly if you have an enough answer for your questions. It’s difficult to earn money on Quora, I did it by doing research and learning from other partners. I added it to my passive income stream. I found medium and vocal media to monetize my writing Making money by writing online was difficult for me. I never tried freelancing but will try in the future. To earn substantial passive income, I started my blog, but it didn’t get any eyes. I invested $100 on my blog and earned nothing. I discovered Medium on google and joined it. First time in my life, I earned by writing online. Writing on Medium is a privilege for me. I have earned $75 on medium; I know the amount is small but it will be more I started putting out more efforts on Platform. I earned, $6 in September $23 in October $48 in November By publishing around 60 Stories. Screenshot by author Recently I have written on vocal media, I am not earning much on that platform but it is always good to stick two or more platforms to a built portfolio for the future. Both Medium and Vocal Media are the best blogging platform, I am practising my writing and earning a good sum to invest in the share market. How earning passive income helped me to pay my bills Will $100 per month change my life? We always look for a bigger amount. Let me tell you if you have proper investments plan, you can double this amount. I use my passive income for further investments in stocks and bitcoins. I take risks; it helps to make more money. At the end we all living for money, which is our priority. Articulating, proper investment plans helped me to achieve my financial goals. takeaways When I look back in my life, I was always out of money and diving in a financial problem, but when I started earning passive income, I’m becoming more financially stable. No college or school tells you about how you can become financially independent and stable. You must carve your way out. It’s time to sum up, our story, Look for a potential passive income source Start growing it day by day Invest time and money to learn new things Invest your passive income in shares and bitcoins Gain Access to Expert View — Subscribe to DDI Intel

https://medium.com/datadriveninvestor/how-i-earned-424-45-as-a-side-hustle-in-my-free-time-640922edc2cb

['Mike Ortega']

2020-12-27 16:18:35.034000+00:00

['Life Lessons', 'Productivity', 'Entrepreneurship', 'Money', 'Finance']

7 Ways to Improve Your Writing in a Foreign Language

Be bold and don’t just use ‘words’ Each language has an infinite richness in its way of manifesting itself. Don’t just stay on the surface. Go deep and look for expressions, slang, spontaneous and natural ways of foreign speech. Do not limit yourself to just one word, when you can use a much more expressive locution instead. This generates a connection with the reader, making him or her identify and affect themselves more by your writing. For this, you can search on the Internet like the following: How to say [insert here an expression of your native language] in [insert here what foreign language you want to write in]. “Language is the road map of a culture. It tells you where its people come from and where they are going.” — Rita Mae Brown Analyze the context of each sentence If in any more complicated situation you end up needing to translate using automated translation programs or websites such as Google Translator, be very careful. Always, in any case, analyze the context. Translating a word in an isolated and hasty way, outside of a specific conjuncture as a sentence, can cause it to change its meaning entirely. Especially because, unlike Portuguese where we usually have a specific word for each situation, in English, the same term can have different meanings depending on the situation. To avoid mistakes, I have two tips! First, after finishing, do the reverse translation and see if the meaning has changed in any passage. If this has happened, fix it and repeat the process until the result is a consistent message. In the second place, we have some sites that facilitate this process. On Linguee and Context, you can see the searched terms inserted in a sentence and see if the meaning corresponds to what you would like to give for the phrase. “Learning another language is not only learning different words for the same things, but learning another way to think about things.” — Flora Lewis Use your own discernment too In addition to automated translators, resources such as Grammarly, which assist with editing and proofreading, are also offered as a way to collaborate with the writing process. Use them to help you, but don’t trust them blindly. They are certainly fundamental tools in building better writing, but they are just tools. We cannot underestimate our ability to judge when something is sounding strange or out of place. Trust your gut. It is worth pointing out that we still don’t have any resource available that perceives 100% the differences of connotation or meaning that we may be wanting to apply, or that has the subtlety of human perception. Especially if it is a matter that can be as subjective and fluid as language. Figures of speech, such as ironies, double meanings, metaphors and personification, can easily go unnoticed. Each word and expression carries with it an infinity of senses that may not be translated with the quality expected by machines. The final deliberation must pass through us! “To learn a language is to have one more window from which to look at the world. “ — Chinese Proverb Understand the language structure This is one of the most important tips. It is implied that if you are studying and producing content in a new language, you already have some knowledge. But what I am reinforcing is the need to know in-depth the formation and syntactic structuring of the language. A good understanding of these particularities can even contribute to optimizing the translations in the programs and sites already mentioned, when necessary. For example, every time I translate something from Portuguese to English in the translator, I add the subject in the sentence. I need to do this because in Portuguese we can often have a hidden subject. This small correction greatly increases the chances of my translation is done correctly. I also need to pay attention to verb tenses, which are much more numerous in Portuguese, and to reflexive pronouns, which function differently. But that is my mother tongue. You will need to pay attention to the structuring nuances of yours! “He who knows no foreign languages know nothing of his own.” ‒ Johann Wolfgang von Goethe Reflect on your message Now, a very serious matter. You need to remember that it’s not just ‘writing’ in another language. You also need to ‘think’ in it. That is, you also need to analyze whether the message you are conveying, in a cultural and social context, makes sense — or is relevant — to readers. For example, some basic references to moments, facts or events, which would easily be understood by a compatriot of yours, may not be understood by a foreigner. Writing is also a matter of making the reader identify with the written subject. Besides, we must consider and, when possible, respect the subtleties of speech. Differences in communicative preferences, such as levels of formality and politeness, mentalities and values, must be taken into consideration. For example, English is a super simplified language, short and objective sentences are used, often with a usual ‘order’ of positioning the words. Brazilian Portuguese — I don’t know about Portugal — has countless ways of writing the same sentence with countless other possibilities of ordering it. In other words, we — generally a typical behaviour of Latin, Arabic, Asian and African cultures — tend to adopt a preference for indirect enunciation marked by pre-requests, justifications, in which the speaker conducts the speech in a circular basis. Meanwhile, Anglophones opt for a much more directive form. Another detail is that in Portuguese we do not need to use verbs like ‘would’ and ‘could’, emphasizing a condition when making requests. We could achieve the polish effect only by the intonation, dispensing the use of specific words, or even making use of diminutives for that. Our speech is also topic-oriented, while in the English language the prominent element is the subject, that is, the interlocutor. I have only used these examples to demonstrate that a language also carries great cultural baggage. We need to pay attention to all these details if we want to deliver the clearest possible message. “If you talk to a man in a language he understands, that goes to his head. If you talk to him in his own language, that goes to his heart.” — Nelson Mandela Pay extra attention If even in our native language, we often slip, writing a text in a language that we do not fully master requires us to try twice as hard. Use the programs mentioned here to help you, read carefully, search and dedicate yourself. I am sure that in the end, the pleasure of looking at a well-written text that communicates the message you want will be worth it. “One should not aim at being possible to understand but at being impossible to misunderstand.” — Marcus Fabius Quintilian In doubt, ask natives To ensure that you are being accurate in your message in all the above cases, as in the case of application in a context, or the cultural understanding of the reader, do not hesitate to ask a native for help! No one knows the language better than someone who has grown up and lived their life using it. Make friends, interact, strengthen your network and whenever you feel the need, ask. There’s no need to feel ashamed. Most are always very willing to help! You should be proud that you are trying and wanting to learn and improve.

https://medium.com/swlh/7-ways-to-improve-your-writing-in-a-foreign-language-895ea169d8e

['Layane Moura']

2020-05-11 09:23:57.128000+00:00

['Language', 'Writing', 'Productivity', 'Writing Tips', 'Language Learning']

How to convert from React-Redux classes to React Hooks, the easy way

Hello everyone! With the recent release of create-react-app v3 and React hooks, I decided to write a tutorial on how to refactor a class component to a functional hooks component. In this tutorial, I will share how I did it. I refer to this as the “easy way” since it doesn't require you to change your Redux code at all. The reducers and actions can be virtually left as is. If you want a more basic intro to React Hooks integration check out my previous tutorial. You can find the project code here. This project uses both Redux and React hooks which will allow you to see the code and differences side by side. Open up the hooks_container1.js file and container1.js files in your text editor to see the differences. I tried my best to match the React class and React hook line for line making it easier to see the differences. However, it didn’t work out perfectly since there are some major differences between React Hooks and React classes. I tried to keep the functionality of both components the same so it will be easier for you to pick out the differences in syntax. Table of Contents TLDR version useReducer and Context When to use local or global state and useState and useReducer How Context Works Directory Structure The Context Object Reducers and Actions Reading and Updating state in React Redux vs. React Hooks Merging the old state in React Hooks Reading and Updating state with useReducer and Redux Reducers Reading state and Dispatching Actions Context with useState Context with useReducer The Easy Way — TL;DR Step 1: For your reducers, export both the initialState and the reducer. Do not export default the reducer. Step 2: Actions can be left as is from React-Redux Step 3: Import all your reducers and their initialState to the root App.js file. Import actions as normal. Step 4: Pass in each reducer and its initialState to a separate useReducer() hook in the App.js file. Step 5: Import the React.createContext() function to App.js after initializing it in its own file. Wrap all child components with <Context.Provider /> Step 6: Next simply cut and paste the properties defined in your React-Redux mapStateToProps() and mapDispatchToProps() functions to the value prop of <Context.Provider /> Step 7: Change the dispatch keyword in your properties from the mapDispatchToProps() function to the name of the dispatch actions function (2nd element in the array destructuring) in the useReducer() hook. Since each reducer will have its own useReducer hook, you will have to match the appropriate action dispatches with the right reducer. Step 8: Do the same thing for the mapStateToProps() function. Change the name of the property to match the useReducer hook. The state value for the useReducer() hook (1st element in the array destructuring) contains the entire initial state from the reducer. You will need to access each property of state with dot notation, and then pass it into a property in the “value” prop. Step 9: Finally to actually use the global Context state in a child component, you first import the original Context object to the child component. Then pass in the imported Context object to the useContext() hook. Save the result of the useContext hooks in a variable. Now you have access to all the properties that we defined in the value prop of the <Context.Provider /> in the root App.js file. Accessing state values in a child component with context: context.stateprop1 Dispatching actions in a child component with context: () => context.action1() Here is an example of a React Redux class container and a React Hooks functional component with similar functionality side by side. Before getting started, I’d like to clarify a few things that confused me when I first started working with React Hooks. useReducer and Context I was confused a little at first by useReducer. I thought by simply using useReducer, I would have automatically mimicked Redux functionality and have a global state. That isn’t the case. It is Context that makes our state global. Context can be used with either useReducer and useState. global state: meaning state persists from one component to another. If you changed state in one component and went to another component, the state would be saved if it is global. If the state is local and you went to another component the state would not be saved. When to use local or global state and useState and useReducer For teaching purposes, I will show you all four possible combinations of local and global state with useState and useReducer. In a real app, I would use the useReducer hook for complex global states, such as authentication and storing data from a server. I would use the useState hook for simpler local state, such as opening up and closing a modal. How Context Works Context predates React hooks and is a way to pass down props to deeply nested child components. Without context, props would have to be passed down to every intermediary component to get to the intended child component. Context solved this by allowing you to pass in a prop to the parent component. Then it would be available to all the child components automatically. You did not have to pass it down through middle man components. And this is essentially how we have a global state. By using the Context in the root component, our state is available to all child components. Since App.js is the root component, and every other component is the child component, the state we defined in App.js is available to all components. It’s important to keep in mind that all the state is contained, initialized and updated in the App.js file. You can call a function to change the state from a child component but it is ultimately updated in the App.js file. Directory Structure and Intro Instead of focusing on how to build this app step by step, I will instead focus more on the differences between the React-Redux class and the React hooks. Here are a couple of acronyms I use and their meaning uS = useState signifies when something is using the useState hook uR = useReducer signifies when something is using the useReducer hook Here is the directory structure. It is a very basic app that has: 1 React-Redux class 1 React functional component that uses the useState, useReducer, and useContext hooks Actions and action types Reducers to use with React hooks Reducers to use with React-Redux a Context file The root App.js file The Context Object I like to have context in its own file since you have to import it to every child component that you use with the useContext() hook. We don’t need to do anything else to setup the Context object, we just need this one function. Also, notice we are not passing in any state to the Context object. You may see other tutorials that pass values to the createContext() function. This is pointless as we will override these values when we setup the <Context.Provider /> and pass in the state to the value prop. Reducers and Actions Now I will show a reducer for use with React Hooks and one for use with regular React Redux. Reducer for use with React Hooks: Reducer for React Redux: Notice in the React Hooks reducer we are exporting both the intialState and reducer. We are not using export default at the bottom. In the React Redux reducer we export default the reducer. Next, we have our actions and action types: Actions and action creators require no changes from React Redux. Reading and Updating state in React Redux vs React Hooks With the preliminary information out of the way, we can now look at the hooks_container1.js and container1.js and see the differences between React Hooks and React Redux in the code. Let’s start off and look at local state for each and see how you would implement a simple counter. React-Redux React Hooks The first thing to note is that we are going from using a class component in React Redux to a functional component in React Hooks. Hence why we don't have the “this” keyword anywhere in our React Hooks code. Since we are not in a class, we can reference the variable and function names directly. In React Redux we initialize the state in the constructor and have a dedicated setState() function. Both “state” and “setState()” are reserved names. This is not so in React hooks. In React Hooks we create our own “state” keyword and setState() function ourselves with the useState() Hook. In the example above, you can think of “value” as the equivalent to “this.state” in a class component. And similar to “this.state”, we use dot notation to access each individual property of state, so the syntax we will be: value.name_of_property When I first started learning Hooks, I used to confuse the useState() hook as the equivalent to setState() function in React Redux. This isn’t the case. The React Redux setState() function is equivalent to the second element in the array destructuring. Which in the example above is setValue() . This setValue() function is how we update our state with hooks. useState() is then just a way we initialize the ability to read and update the state in a functional component. This previously was only available to class components. Merging the old state in React Hooks Another important thing to notice in the React Hooks example is that I am using …value before updating the state in the increment and decrement functions. This is the spread operator, that passes in the entire flattened previous state to the setState() function. I did not need to pass in the previous state in the React Redux example. When we update a state property in React Redux the new state property is automatically merged with the old state properties. This does not happen in React Hooks. When you update the state in React Hooks, a new state is created. You see in the React Hooks example we have 2 state properties: local_state_prop1 and local_state_prop2 . If we update the state with only local_state_prop2 and not pass in …value then a new state will be created that has only local_state_prop2 . Meaning our local_state_prop1 will simply just be deleted. So when converting state from React Redux to React Hooks, you will need to pass in the entire previous state with the spread operator when updating a single state property. Reading and Updating state with useReducers and Redux Reducers We can now compare reading and updating state with useReducer and Reducers. We are using the same reducer as in the above example. A reducer with SUCCESS and FAILURE action types that changes stateprop1 from true to false and vice versa. useReducer Hook React Redux As mentioned in the intro, even though we are using useReducer() in the functional component, we are still only updating the local component state. I will show you how to mimic Redux functionality with Context and have a global state in the next section. It is important to keep in mind we are still only updating the local state here in our Hooks container even though we are using actions and reducers. On the other hand, in our React Class component, we are updating the global state since we are using Redux. So the first difference you will notice with useReducer is that we have to import our reducer and initial state and pass it into the useReducer hook, which is something we don't do with React Redux. In React Redux we just use the connect() function. Reading state and Dispatching Actions Next, to dispatch actions in React Hooks, we use an arrow function then dispatch our actions in the body of the function. You can dispatch actions directly in the onClick() event but having the dispatch in a function will make your code more readable. In React Redux we set properties in the mapDispatchToProps() function, then each property is an arrow function that dispatches actions. You will notice that we pass in actions and actions creators in the exact same way to the dispatch function in both React Hooks and React Redux. There is literally no difference which is why we didn't need to change our actions at all. I have included all the ways of dispatching actions as a comment. The only difference between React Hooks and React Redux is that the “dispatch” function name is reserved in React Redux. In React Hooks we create our own “dispatch” function name through the useReducer hook. To call the dispatch function in React Redux we use the syntax this.props then the name of the property in mapDispatchToProps() function. In React Hooks we just call the dispatch function name directly. To read the state in React Redux we do this.props and then the name of the property in the mapStateToProps() function. The name of the property holds the value for a specific property in a specific reducer. In React Hooks we just do the name of the state value. This is the first element in the array destructuring in the useReducer hook call. Then the name of the property we defined in the intialState in the reducer. Context with useState Now I will go over Context which is how we setup a global state. It is important to note that Context is not part of React Hooks. useContext() is a React Hook, but Context itself is not part of React Hooks. Context is simply a way to pass down props from a parent component to a deeply nested child component. See the “How Context Works” section at the beginning of this tutorial for a full explanation. Also, I will not be making comparisons between React Redux and Context because Context does not have an opposite in React Redux. I will show you how to implement a global state with Context using both the useReducer() and useState() hook. We will first start off with the using the useState() hook to setup a global state. We will begin setting up our global state in the root App.js file. We will first import the Context object we setup in the context.js file. We will also need to import our Hooks functional component. We can just set up a simple counter for now. Our useState() hook is setup as usual. In our JSX we are wrapping our <HooksContainer1 /> with the <Context.Provider /> element. This is what allows us to pass state from App.js to child components. We also have 3 properties supplied to our value prop. 1 to hold the state value and 2 properties to change the state. Notice that we don't use the useContext() hook in App.js. The useContext() hook will actually be used in child components to read and update the state. You can essentially think of the value prop as both the mapStateToProps() and mapDispatchToProps() functions combined into one because of the value prop holds properties that allow you to read and update the state that can be called and accessed by the child component which is exactly what the mapStateToProps() and mapDispatchToProps() functions do. Now let's look at how we would use this Context object in a child component. We first have to import our Context object at the top. This is the original Context object that we created with the createContext() function, not the <Context.Provider /> we just setup. Then we simply pass this Context object to the useContext() hook and save it in a variable. This context variable now has all the properties we just defined in the value prop of the <Context.Provider /> . To access the properties of the value prop we can just use dot notation. For example, to access the state value here in our child component, we use the syntax context.valueGlobalstate_uS . Note that valueGlobalState is the name of the property we defined in the App.js file in the value prop. valueGlobalState is the property that holds the value of the state which in App.js we defined as valueGlobal_uS . Similarly, to change the state we call the property name and not the name of the function we set in App.js. I have intentionally kept the property and function names different so its easier to see how Context works in the child component. This is it for using Context with useState. I will now demonstrate with useReducer. Context with useReducer Using Context with useReducer is essentially how we achieve Redux functionality. In order to avoid confusion, I will setup a new reducer and actions for this. So we have a simple reducer that functions as a counter. Now we can set up the useReducer hook in our App.js file and we will set this up in the exact same way that we set up useReducer in our Hooks container. We import the ContextReducer and its initial state and pass it into the useReducer Hook in App.js. Because we are now using Context we will not import our Context Reducer to the child components. The state will be changed here in our App.js file and will simply be passed down as props. We set up our properties in the value prop in the exact same way that we did when we used Context with the useState() hook. The actions are also dispatched in the exact same way as we’ve seen before. Now for our child component: As you can see, reading and updating state with useReducer() hook is very similar to the useState() example. We can even use the same context variable we used for useState() , we don't have to initialize another one. To update the state we simply call the property name we defined in the value prop of the provider. This updates the state in App.js. Because we are updating our state in App.js we don't have to import the ContextReducer here in our child component and pass it into the useReducer() hook. Reading the state is a little bit different. Since valueGlobalState_uR contains our entire state, we have to specify a single property of state which in this case is context_prop1 . And this is it! After this you can read and update the state in any component in your app using this same pattern, allowing you to mimic Redux functionality essentially. For a 100% Free Video version of this tutorial and more in-depth React Hooks content see my Udemy course or Youtube playlist: https://www.udemy.com/react-hooks-with-react-redux-migration https://www.youtube.com/watch?v=l8ODM-KoDpA&list=PLMc67XEAt-ywplHhDpoj5vakceZNr8S0B

https://medium.com/free-code-camp/how-to-convert-from-react-redux-classes-to-react-hooks-the-easy-way-eca2233e0e7a

['Mohammad Iqbal']

2019-05-15 15:47:20.821000+00:00

['React', 'Technology', 'Productivity', 'Tech', 'Programming']

The Place Where Everything Feels Cold and Empty Is Not Far Away

The Place Where Everything Feels Cold and Empty Is Not Far Away No one reached it yet, as it’s moving whenever they moved Photo by Guillaume Bleyer on Unsplash There was a group of men, whose hearts never new the best and no matter how much they desired it they didn’t know where is it. Their hopes clutched to one experiment in which they will seek the worst, to know its contrary and peruse it. They looked for the worst in men, from the dreary traits to the heroic merits. They searched day and night with one goal and aim: To discover the truth. And when they got tired, when they decided to stop, they turned to see the truth sitting behind them all along, then they lowered their heads and looked into themselves. The surprise hit, but not an actual surprise because in most of the occasions we predict the bad news and we pretend we are shocked. The men saw nothing in themselves, but the worst of the worst floating and swimming in their veins. Their eyes scanning the lengths of their bodies, as if they expected to find anything else. Emptiness. And I’m glad they gave it a name. They stopped the research and looked to one another, to the only thing they had in common. It linked them like a thread of silk barely stretching to unite them by their sudden, semi-new goal: Finding the worst in themselves before touching it in others. And since they turned the project down, they feared the thread would perish. A long, awkward silence filled the place, and until now flies only flew around them increasing the tense. A long, sweaty, thick hand stretched, or that’s the description from one’s mind. It hung up in the air, as to mark a clothes hanger — a thick one. Two hands stretched, then three and slowly one by one, they shook hands and tried to smile. The days hastened by, and the group of men had more silk threads and less envisions of sweaty hands. And they were astounded to look into themselves and find the emptiness fading away leaving words in its place: Relationship, friendship, and love — ship, perhaps? They were not certain yet. And the moment came in which they broke apart and didn’t shatter. They found the contrary.

https://medium.com/the-pom/the-place-where-everything-feels-cold-and-empty-is-not-far-away-4ae4c955940a

['Abdullah Alshawaf']

2020-05-06 14:36:19.556000+00:00

['Short Story', 'Relationships', 'Mental Health', 'Poetry', 'Storytelling']

I Thought Gay Celibacy Was My Only Option — I Was Wrong

The most difficult part of convincing someone when you are begging for food is figuring out what kind of face to make — appearing both in need and deserving somehow. Look too desperate and they will think you might make a grab for their purse or ask to move into the spare bedroom. Too responsible and they’ll wonder whether you really need help at all. I begged in France while living with a religious order. “We have nothing to eat. Do you have anything you could share?” I would smile and hold the straps to my backpack like an earnest schoolboy. Hungry, but honest. I had never begged on the street before and was struck by how humbling it is — asking strangers to keep you alive just because they can. And you can’t. “No,” the eighth woman I asked scowled at me from behind her front door. “Go away.” I wanted to tell her No really I have no food, no money. I don’t have, like, options here. Do you want to feel my stomach rumbling? Check my pockets for a wallet? Eventually, a man invited my companion and I into his house and began making each of us a sandwich with thick slices of cured ham. Standing in his kitchen he asked us where we were traveling and why we were begging. “We travel simply, and go out two by two like Jesus sent his disciples,” Brother François responded. “Yes yes,” the man waved his hand. “I assumed that by your clothes. But why?” He looked at me like a cardboard American Happy Meal amidst his table of crusty bread and smelly cheeses as he waited for Brother François to finish translating. “Why have you come all the way across the ocean just to beg food from me?” I hesitated and imagined myself answering him the way I had never been able to do when anyone asks me why? Honestly. “Because I’m gay,” I would say. “I have no other choice.” He would nod appreciatively and say how much better begging for ham sandwiches and smelly cheese on another continent must be than being gay on your own. Most of my life I have not been able to articulate the reality beneath the surface. Nobody I knew ever wanted to know why gay people do the things we do, so I gave him the version I assumed he would like. “I may be a beggar, but I still have good taste.” I winked at him. “Where else would I come to eat besides France?” As we left the man’s house Brother François and I said a prayer together in thanks for his generosity and God’s providence. God provides for our every need, if only we would ask. That is the promise I was putting to the test. If you were told by those you trusted most that your sexuality was broken, was a threat to you and those you loved, how far would you go to protect the world from it? Would you hide it from your friends? Abandon anyone you ever fell in love with? Tell your family you had to leave them because you feared how you were hurting them? I did. I believed that promise. God will provide. You could say I ended up begging on the other side of the world because I took the Catholic Church seriously about my being gay. Maybe that’s not entirely fair. France is not really the opposite side of the earth from Texas, even if substantively it is. But when you find yourself a gay Catholic man, you are told you only have three options. Become a priest for life. Become a monk for life. Or stay single for life. Celibacy — complete sexual abstinence — being a requirement for all of them. I guess I was someone sincere enough to try all of them. Pope Francis shook the world’s assumptions about how the largest Christian denomination thinks about homosexuality with his famous “who am I to judge?” comment, though official doctrine shows little hope of changing. Catholic or not, millions of LGBT individuals and their families are impacted by an organization with such an extensive moral impact on the world. I tried the Church’s prescription for our gay lives, and what I can say definitively as one who actually followed it is, the official rules do not always work. Growing up Catholic, I learned that life is about more than just you. There is more to existence than your own experience of it. More to worship than your personal tastes for it. More to human purpose than your imaginings of it. They call it Tradition. Basically, people — mostly men, though with plenty of exceptions — had been thinking about this for a long time before you or I came along. And it is better to find a way to line yourself up with their consensus than to go your own way. That is what being a church and not just a belief was all about. Linking ourselves together in the faith that absent the egocentric leanings of the individual, we might actually recover a natural order to life. And what that consensus found in my case was that being gay was, well, not okay. I found I was gay about the time most boys start to discover there is much in life to wonder and terrify them. Eleven, maybe twelve. I didn’t have any words for it, I just knew the way I looked at some of the boys differed from the way any of them ever looked back at me. When it dawned on me a few years later that the very worst insults those boys would call each other — gay, queer, fag — actually applied to me, I learned that even if there were words for how I felt, they were better left unspoken. I did eventually come out to my folks and a few friends in high school, though it was far from the way I would have planned. There was no celebration or relief, and certainly no pride. At that point I had never met a single gay person. Not knowingly, anyways. Tired of faking my way through girlfriends and tortuous school dances, I turned to the internet. Back before there were apps on your phone to tell you how close the nearest match might be, I lied about my age and found a college student a couple towns away who would buy me dinner and take me to a movie. I was sixteen and my leg could barely stop shaking I was so frightened. On our second date I told my parents I would be staying the night at a friend’s house and instead spent the night with the first gay man I had ever met. It was Valentine’s Day and when I got in his car he handed me a dozen roses. I must have looked at him as if he had given me a baby giraffe. I never imagined someone in the world might buy me flowers. When I woke up the next morning my phone had several dozen missed calls. In my haste I had forgotten to tell my friend to cover for me if anyone called and my parents had spent the whole night desperately looking for me. Arriving home, most everything came spilling out under my parents’ interrogation. I had been with a boy. I am gay. I don’t know, the Church has been wrong about other things like Galileo, why can’t this be like that? My parents seemed equal parts exasperated at the night I had put them through and concerned about what this coming out might forebode. The treatment for both, it seemed, would be to start taking church more seriously. Up until that point my family had gone to Mass most Sundays, but it was more akin to something inherited, like being Irish, than something chosen. Whether as punishment or remedy or both, my parents wanted church to become something personal. And with some time, I genuinely grew to like it. The parish my family attended was another town over and had a big youth group which combined some of the more engaging practices of the surrounding nondenominational megachurches with the old school traditions of Catholicism. We had smoke machines and incense, adoration with our altar calls. I had a genuine conversion experience and dedicated my life to God. Finding a new group of friends who were all finding a way to be Catholic and teenagers at the same time made me feel like I wasn’t so alone. Which was enough to help me set the gay stuff on the shelf for a while. Like a box I knew I could ignore but eventually find again if I ever needed to. I didn’t really know what to make of the fact that I now felt closer to the Church that thought I was incapable of romantic love and intrinsically disordered. But I was seventeen. I knew not everything had to be figured out right then and there. No one at church needed to know I was gay. I could just keep that part hidden and see where things led. So I started praying regularly. I tried therapy — not the conversion kind— but with a woman who told me I would only ever be happy in life as a celibate man. I got involved in leadership. And I did what I could to align my life with how the Church asked me to. By the time my freshmen year of college rolled around, I started to feel a nagging in me, like an itch just out of reach, whenever I was alone, talking with God. I had gotten to know many priests and I saw the positive impact they were having on people’s lives. In time I started to feel like God was asking me to give it a shot. I wish I could say exactly where this was coming from. Maybe it is just that so many of the priests I knew were genuinely honorable men with purpose to their lives. Maybe I rushed into it. But at nineteen I joined a seminary in Minnesota, to begin the eight year process of becoming a priest. There were over one hundred of us. Men from all over the Midwest and South. My roommate when I arrived was a frat boy from Oklahoma with an infectiously charismatic perspective and played the banjo. Officially, all of us were getting bachelor’s degrees in philosophy, though the daily schedule revealed a bigger plan. There was more to becoming a priest than classes. Prayers began at six a.m. There were times of “formation” and times of bonding. The rector — the priest in charge of the seminary — believed the American Catholic Church had undergone a crisis of leadership. Its cure must be a generation of priests who would remember what it meant to be real fathers for their flock. No more “liberal” theology. No more comfortable and insulated lives. Be a man and get out into your parishioners real lives. When I arrived for my first weekend, the rector held a conference for all of us new seminarians. It covered the basics of his vision and what to expect, as well as some potential pitfalls for where life as a seminarian could burden a nineteen year old as unprepared to pastor a flock as he was to pass a philosophy class. How to navigate dry time in prayer and former girlfriends writing forlornly from home, new schedules and notorious professors. He treated us like the future front line soldiers in a battle for the very heart of the culture we sought to serve, and we loved him for it. On the second day of talks he mentioned that, statistically speaking, a small portion of us were probably gay. Of course he didn’t use the word “gay.” Officially speaking, the Catholic Church uses the clinically dry term same-sex attracted. As in, “some of you probably struggle with same-sex attraction.” Identifying as gay is thought of as being a kind of all-encompassing characteristic with a whole behavior set of which the Church disapproves. But being same-sex attracted, the rector said, would be an inherently isolating quality, and he recommended talking to one of the priests on staff about it at some point. So the first time I had a meeting with him in his office, I told him I was indeed struggling with an attraction to the same sex. My heart was pounding. It had been over two years since I had mentioned my sexuality to anyone. His response was one of genuine compassion. He looked me in the eyes and told me it must be hard and was nothing I had chosen on my own. Concerned about my well-being going forward, he suggested we develop a sort of not-so-subtle code. If I ever felt like life was becoming more than I could handle, I would simply say, “Father, I’m at Defcon 4.” Or three. Whatever the state of alert might be. The concern for me was real, though I rarely felt he was someone I could — or should — confide in about my sexuality. He was a good priest who cared about me deeply, but I knew what type of man he wanted his seminarians to be. Was the comment when he and I were alone about how annoyingly gay a campus administrator was a hint for me or just something he felt he could confide because I would understand? I didn’t know, but I did my best to impress him and repress the parts of me I knew disappointed. Wandering the campus alone late at night sometimes I would pray and cry and smoke a handful of cigarettes beneath the massive Marian statue behind the school chapel. I hated the habit but it felt good to finally have some kind of manifestation of the ugliness I felt inside. I begged for a change, for any glimpse of healing. And when the sun came up I would leave a pile of tobacco ash at the statue’s feet like some kind of intrinsically disordered offering of burnt incense. Eventually the time came to decide if I would continue on to the next four years of seminary before becoming a priest. Despite my inner turmoil, I had achieved a certain kind of esteem in the seminary, a kind of big shot in a cassock. Leaning on my status, it was for those years surprisingly easy to overlook just where all of this was leading. In the end I had to ask myself, did I actually want to spend my life in the daily tasks of a priest — hearing confessions, celebrating Mass, visiting the sick, and baptizing babies? When I finally sat down and looked honestly, after almost four years of preparation, I had to say that I liked being a seminarian more than I could ever appreciate being a priest. I liked the community, the studying, the hoorah sense of purpose. If it was God that was giving my life some direction, I knew there were no signals I should end up a priest. After graduating I got a job back in Dallas teaching at a local Catholic high school. I was hired to teach morality and social justice, coaching the JV baseball team after hours. At the time, morality was a junior level course at the school, so I started tackling the principles of behavior with teens at the same age when I had first started to explore my own sexuality. The timing wasn’t lost on me. This time I was all in on Catholic morality but set out crafting a class where my students were challenged to develop their own conscience even as I broke open official Church teaching. As any teacher will tell you, it was exhausting work. I would stay up late into the night planning a lesson on immigration only to find myself inevitably sitting on top of an empty desk, sleeves rolled up, guiding a vigorous discussion about whether extraterrestrials could have souls. The bigger problem was life outside of the classroom. In seminary I had a built-in cover. When you are training to be a priest, your sexuality is out of bounds. Nicknames like Father What-A-Waste may have been joked about, but people respected the idea that you were off-limits. Suddenly, back in Texas, I was forced to explain why I was so delaying jumping back into the dating life. Every mom in the church seemed to know of the perfect girl. I was young, good-looking enough, and I even used to be a seminarian. In church life, that’s the jackpot. Girls would openly admit being on the lookout for former seminarians like a forbidden fruit put back on the menu. I just wasn’t the least bit interested. And couldn’t tell a soul why. Friends’ weddings were the most bittersweet of occasions. I was in my early twenties so there were plenty to attend, but I always knew they would be followed by a depressive funk. Most of my friends were involved in church, so they were not only a massive party, but had been marinating for years in the knowledge that this was a divine act. Not just a decision, but a vocation. The priest would preach on the heroic and beautiful sacrifice the spouses were making. They would be open to kids. They would live for each other. They would be the very foundation of humanity. I sat through those weddings wondering why I was incapable of all those things. What kind of person I must be to be incapable of such love. As one wedding ended, when we all bowed our heads to pray, I closed my eyes and imagined what it would be like to be standing in front of the altar myself. Wearing a tuxedo for the first time since I took Sarah to prom. I pretended I was holding my fiancée’s hands, afraid to look away from his eyes for fear the moment might not last forever. My friends and family would all laugh because the priest was telling us to do something but we were too caught up to notice. I remember sitting down as my friends walked down the aisle, my head in my hands and tears streaming down my cheeks. To be honest, what I sensed imagining my own wedding was not relief. It was the first time I had ever actually allowed myself to picture it happening to me, and it felt like the dirtiest thing I had ever done. I considered confiding in friends about being gay, but thought better. It was a small enough community that word would inevitably get back to the Catholic school where I worked. I would see news reports about a choir director or an English teacher was shown the door after administrators found out about a boyfriend or students just found out somehow. People from my church would usually share the story on Facebook with a warning about the creeping lack of religious freedom if anyone wanted the teacher reinstated. But what kept me closeted even more than a fear of getting fired was a fear of losing my community as well. Texas has its progressive pockets, but they felt lifetimes away from my town. I didn’t know what would happen if people found out I was gay, but I could guarantee they wouldn’t stay the same. At least like this I had a happy life on the surface. There was a lake nearby I would drive to when feeling depressed. I would go sit with my feet in the water and imagine a world where I wasn’t hopelessly broken. Sometimes a close friend or family member would casually remark how gross a gay kiss on TV was and it would be enough to send me hyperventilating to the water’s edge. How could I be so well-liked on the surface and reviled underneath? I loved my job and accepted that I would have to be single for life, but loneliness would gnaw away at me at night until I began to realize I would not be able to keep up this path for much longer. A priest once told me that gay couples were much more violent than straight couples, that they had much higher occurrences of domestic abuse. I told him I didn’t know that. And it’s true, I didn’t. I’ve looked it up since and it turns out the statistics are incredibly inconclusive. But he seemed quite pleased to have discovered this fact. He didn’t explain why he thought it was important but I think I understand. If gay relationships are inherently wrong, then there must be something wrong about them. Catholics can get pretty abstract when talking about this stuff. You start floating in a sea of terms like “procreative” and “unitive” and “telos.” It helps to just be able to say “Hey, romance makes them more violent.” It’s not true, but it’s helpful. What I know is that listening to this priest I looked up to telling me about this violence I had curled up inside me like a dragon sleeping in his cave waiting for anyone foolish enough to say they loved me felt like I was being hollowed out. I didn’t know there was no good evidence to support his claim. I trusted him. I imagined myself cooking a meal as my partner came home, turning and punching him in the face as Tony Bennett crooned in the background because he forgot to pick up milk on the way home. I had never been in a fight before in my life. Is this what awaited me if were to fall try a relationship? Forget going to hell. Were those my only options? Stay single and alone or become a monster? When I was in high school I once came close to driving my car into oncoming traffic. It was dusk and the steady stream of headlights whooshed by, each one like an invitation heading straight toward me only to miss at the last moment. I knew that would be an awful way to do it, probably taking a bunch of other lives just because I didn’t want keep on living mine. But the desire for some relief, any kind of break from how much I hated myself for the way I was — perverted and incapable of love — in that moment I would have welcomed the crash. I made it home safe that night and even though for years I would wish I could die young instead of letting this loneliness go on, I knew deep down that I shouldn’t let myself get to that point again. Where the headlights seemed to be calling out to me. There had to be something better than killing myself. Even if it meant leaving my job teaching and doing something drastic. On the surface I was calm but inside the rubber bands of my stamina were being stretched to their raw ends. Soon, I could feel, they would snap. During a semester studying abroad in Rome, I had gotten to know a religious community based in southern France. They were a new branch off a very old order and I immediately felt at home amongst them. Joy radiated from their bones even as they begged for their food and travelled by hitchhiking. They were like the old stories of the saints I had grown up with come to life. When I realized my life alone as a single, Catholic man was unsustainable, I wrote the order to ask if I could join. To prepare for entering, I sold all my belongings and said goodbye to my friends, knowing I would probably never see them again and hugged my family not knowing when or where the next time together with them might come. They were an old school community in that respect, you left behind everything and everyone, sending a letter a month to keep in touch during your first year. Photo by Cagatay Orhan on Unsplash Nestled in the foothills of the Pyrenees, the motherhouse of the community was simple and beautiful, with living quarters on opposite sides of the property for the women and men who made up the order. I was given a room with a small, handmade desk and chair and a wooden chest that doubled as my bed. There was a small icon and a crucifix on the otherwise blank plaster walls. Sitting down on my bed at the end of my first night in France there was only one prayer on my lips. What the fuck have I done? I decided I had come too far and given up too much not to be honest with the community. So I confided in just about anyone who would ask that I was near certain this was not going to work out. It was more than being homesick — I knew in my bones I wasn’t made to be a brother. The counsel I received was unanimous. Give it one year. It simply takes that long to know. Relax, and let things run their course. But if there was one thing that I saw clearly now that I was walking through the tall grasses in those ancient hills, it was that I had run away from the problems that came with being gay. Five thousand miles and an ocean away, I hadn’t escaped who I was, only amplified it. Between meals in silence and the hours each day spent quietly in work and prayer, I saw myself more clearly than ever. Saw my gifts and my weaknesses as they echoed around in my head. I didn’t need a lake or a late-night cigarette under Mary’s stoic gaze to see the whole me. My days and nights had become like a sense-deprivation tank for discernment. And in the silence I could hear the whispers of reality roaring. There were plenty of times when I did think maybe I needed to stick it out. That I might have hidden my poor intentions in joining the community from even myself until they were staring at me from every corner of my bare cell on the first night, but what if God still had a plan for me with the community despite all that? I would sit in the quiet beneath a gentle paraffin lamp and watch the humble instincts of the brothers and sisters and realize there was something undeniably beautiful there. Young girl in a Roma camp in France. Photo by the Baltimore Sun. In the winter we built a tiny cabin out of a trailer for a group of the sisters in nearby Toulouse who had been invited to come live in a Roma — gypsy — camp there. They saw the sisters begging for food and recognizing kindred spirits, people who saw the world from their perspective, welcomed them into their camp on the outskirts of town. One of the most reclusive and reviled groups in all of Europe — seen by society as nothing more than foreign beggars and thieves — and the community had the humility to say it would be an honor to share a home with you. How do you not see the very heart of the Gospel in that? How do you not fall in love? But then I would have moments with the community that would remind me that I could never in my heart say the vows that would make me one of them. The foundress of the community told a handful of us a story of a time when a family close to the community lost a son who was openly gay to suicide. The family asked if the community would perform the ceremony of the funeral, an act that for the brothers and sisters, would be a great affair, keeping vigil the whole night in prayer with the body. When the funeral was over, another local woman came up to the foundress, concerned, and said, “Sister, I didn’t realize the Church approved of homosexuality now!” The foundress gently explained that a dignified funeral did not, in fact, signify a major change in Catholic teaching, but she then reflected to the rest of us gathered around for the story, that had she known it would have caused such scandal and confusion, she would never have agreed to allow the community to perform the funeral. I understood a simple woman’s disorientation about the implications of the funeral. But I hugged my knees that night and rocked against the wall of my cell, wondering what kind of person I must be if this community I loved so much would willingly build a home in the mud on the tattered edges of a city with the Roma but wouldn’t bring my cold body before God in their church if the neighbors knew it had been with a man. How could I join for life a community that wouldn’t stand by me in my death? After three months, I requested a meeting with the head of the brothers and in a small chapel huddled around the fireplace I spoke my best French and he his best English. I told him I thought it was time for me to leave, that I was gay and had realized that I had come here more to escape that reality than to embrace another. But, I told him, I didn’t want to leave without the community’s blessing. I still had enough of those old Catholic instincts kicking around to remember even this decision was not just about me. Discernment in a religious order is a two-way street, with the community choosing the individual as much as they choose the community. With a great deal of affection in his eyes he asked for three days to pray about it, and told me he would get back to me with an answer. When we sat down again, he told me he agreed it was best for me to leave. And within two days I was back home in Texas. It might seem reasonable to ask, why not try another community? If I were really committed to following Church teaching, just because one group did not fit, would that mean another could not be right? I suppose all I can say is, yes, it would. Ten years of emphatically imperfect submitting to Church authority and only being driven closer and closer to a hatred of self and hopelessness for any future I might have and I began to see those headlights calling out to me again. One night I cooked a quiche for the brothers when a visiting Polish man interrupted the silence of dinner to praise me for how much he enjoyed it. I whispered a thank you to him, looking down at my hands laying in my lap. “You don’t get very many compliments, do you?” He said, baffled by my muted response. It wasn’t true. I was used to getting them all the time. But I realized then I had basically decided the best hope I had surviving celibacy was finding a corner of the world where I could disappear and kill off as many of my own desires and dreams as possible. Which is not to say that a religious order inherently destroys personality, only that I had grown so distrustful of my own, that I found the most extreme place I could to lock mine away and minimize its expression. You would think that when I arrived home in Texas I would feel relief. But after the joy of seeing my family and friends settled down, what was left was a kind of anger and frustration that had long simmered beneath the surface, and was now undeniable. I had done everything there was to be a good Catholic. Or at least a passable one. A Catholic who was irrevocably gay but desperate to avoid hell. I tried to become a priest. I tried to live celibate and single. And I tried to join a religious order. Each led me farther from reality, farther into a twisted and masked version of myself. Back home, I struggled to find a community and a routine that would help make sense of this new reality I found myself in. I tried writing, but when I took a position criticizing the way many Catholics were treating gay people on social media and in person during the firestorm surrounding the Supreme Court arguments on LGBT rights, the reaction in my hometown was quick and strong. Some agreed, but many claimed I had crossed a line and treated those just standing up for Church teaching unfairly. I suppose that was a kind of line for me too. If I couldn’t suggest treating gay Catholics with a little more empathy without it causing controversy, then, I realized, I couldn’t pretend this was a healthy place for me to call home any longer. I needed to get out, and the farther the better. I left the country again, but this time, instead of running away from myself, I was retreating in the literal sense. Regrouping to where I could learn to be me. That refuge just happened to be in the murder capital of the world — Honduras. The Church I was so deeply a part of — and which was so profoundly a part of me — believed being gay was not actually how I was made to be. And yet no matter where I went, it seemed indisputably at odds with the life I was expected to live. I was convinced the key to figuring out who I really was — no matter how anyone felt I was made to be — would depend on getting back to Gospel basics. Love. Humility. Service. I felt far from God and from the Church, but maybe if I could just go be a companion to some orphans, away from everyone that wanted to tell me how much I didn’t belong, I might find some direction again. So I signed up as a two year volunteer at a children’s home on the northern coast of Honduras. I went south with a plan. I gave myself a year to adapt to life in the tropics, on a Catholic home for abused and abandoned children. But once I had gotten a decent grip on the language and found a kind of balance amidst the new community where all my fellow volunteers knew I was gay and the kids had at least started to trust me, I got to work. It was time to to take off the shelf the box I had placed up there when I was sixteen. I was ready to dive deep into what the Catholic Church really teaches about homosexuality and not fear what I might find. What most terrified me was not that I might agree with the Church’s logic, but that I would find it lacking. That the biggest part of my life might have a flaw. Where would that leave me then? I had spent a decade trying to position myself where the Church would approve of me. Finally I gave myself permission to examine where the Church stood with me. I spent several weeks pouring over all the relevant Scripture passages, the Catechism quotes, the Catholic intellectuals. After my days with the kids of the children’s home, I would spend my nights with Ratzinger, Weigel, and Wojtyla, then wake up early before the day started with Neuhaus, George, and Congar. I analyzed and summarized the best arguments against gay marriage they and others had come up with, writing late into the night. Then I read those who precisely because of their faith, disagreed. Catholics. Protestants. Anyone willing to take up their arguments on the merits. Catholic analysis of homosexuality is more nuanced than it is often given credit. Probably because there is so much reductive and damning reactions coming from religious sources, it is lumped in with the larger gay = bad narrative. In reality, the Catholic Church does not teach that all gay people are bad, or even that they have chosen their same-sex attraction. Rather, the language goes, they are “intrinsically disordered.” A distinction is made between the desires we experience, and the actions that might be taken to satisfy them. Sort of like the difference between feeling attracted to your neighbor’s wife and actually sleeping with her. Except instead of the prescription being waiting for the girl that’s right for you instead of stealing your neighbor’s, it turns out every girl in the world is already taken and your fate is to feel attractions that would always and everywhere be wrong to act upon. And that singling out of the gay experience was what I ultimately realized I couldn’t agree with. The part about the Catholic Church’s line of thinking that had so crippled me emotionally, driving me both to think I was better off without my friends and family and holding me deep underwater in bouts of depression — was the belief that I was incapable of romantic love. I have often been told that I am more than just my sexuality. Catholic priests have to be celibate, why should I be so different? And it is true that there is so much more to a person than their desires for sex. But that’s exactly the point. To fall in love. To build a life together. To challenge each other — and if you are believers — to bring each other closer to God. To raise children in security and affection. To feel the peace of knowing that you will try to be there for each other through everything, no matter what. These are not small things. Those instincts and emotions and desires are there in me just as intensely as anyone else, but I am told that I am incapable of all of them. If I feel them towards a man, then they are intrinsically disordered. That if I were to do what comes naturally to everyone else, it would be a most unnatural and abominable thing. In fact, it would be a threat to everyone else’s love and the Church must defend the entire society against it. That it would be self-destructive, not self-giving. That it would cut me off from God, not bring me closer to him. That, in truth, it would be better if I not even try. What does that really say about a person? And how is it supposed to make me a better Christian? The comparison with the celibate priest is irrelevant, for he is offering those things up to God. I, on the other hand, apparently have nothing to offer. So I took an honest look at my own life. This was the one step I had been hesitant to do for so long. I know it would have come instinctively for most, but I had always resisted using my own experiences as evidence. It felt so subjective. Better to stay abstract. But finally I realized that if the abstractions have no grounding in reality, if they cannot play themselves out and actually work, then they are worthless. There is a famous GK Chesterton quote where he writes, “Christianity has not been tried and found wanting, it has been found difficult and not tried.” Which is probably true on most fronts, but is also the type of adage that could be claimed by anyone not satisfied with how far someone else is willing to go. But what if there was a mandate that was found not difficult, but impossible? Oh sure, I could have learned to clench my teeth and push on a little longer. But the truth is, I’m too Catholic for that. For one, I always knew deep down that if I was veering in the direction of desiring suicide, I had gone too far. That the road was leading to a place I was never meant to go. I refused to let myself follow a belief system that broke me so much I preferred death over life, and I could feel myself craving a quick exit. But also, I knew that Grace, if real, should flow freely. That while nothing good in life is easy, if God is with you, he will help you. Yoked, you will manage the load. When I looked back on my years leading up to Honduras, I realized I had surely not managed. I was a living example that proved an exception to the official rule. You could do everything the Catholic Church asked of you, and still end up miserable, broken, and hopeless. It wasn’t until I returned home from Central America that I let myself try something I hadn’t done since I was sixteen — go on a date with someone I actually wanted to be with, and who wanted to be with the real me. I want to be very clear, though. I am in no way trying to imply the paths chosen by other gay Catholics are false. Some gay men may be incredibly happy as priests. Some women and men may find a deep fulfillment in religious life or a celibate single one. My point is merely that I cannot in good faith claim one of those will work for all of us. It simply won’t. I think there is a way forward for the Catholic Church as an institution which may not involve overnight change, but does learn to listen to those of us that have taken its prescriptions about our homosexuality seriously. What does that actually look like in our lives? Is it working or are the depression and suicide numbers silently disappearing sincere parishioners from amongst the pews around you? And for those of us that have decided to stay Catholic and not demonize our sexuality, are we happier and healthier by the Church’s own standards? If you examine us by the fruits of our actions, looking at more than just our relationships but our whole lives, what do you see? There are many of us still amongst you. Pope Francis has ushered in a new tone of listening which parts of the Catholic Church are beginning to heed. But if you are afraid to truly look at our lives, what does it say about your own commitment to the truth? The fact is, most Catholics I know will admit there’s some kind of gap between all that intrinsically disordered business and what they see in their gay friends and family members. Their children are not the monsters they have been told they are. They are a twelve year old girl or boy, in need of some love, and desperate to know they will have someone to love too. Sometimes I imagine being given an option. I could go back and become that twelve year old child, but this time not born Catholic. Raised some belief that never taught me I was intrinsically disordered and that I could fall in love and raise kids just like the rest of the world. Or I could become that twelve year old boy, but still Catholic. Do it all over. Smoke cigarettes under Mary’s stony gaze and cry by the lake and be told my funeral would be a scandal best kept private. But the Church would learn something from it. And the next generation of gay kids raised Catholic would have it different. Have it better. Which would I choose? Without hesitation I would choose a whole lifetime of that pain and never know its relief if it meant those kids would be able to love themselves. It would be worth every damn day. Because after all, life is about more than just me. Being Catholic taught me that. That time I spent knocking on strangers doors and asking for food, asking them to keep me alive, just because they could, would bring me back to a scripture passage about a foreign woman who asked for a small mercy for her child from Jesus. He tells her coldly, if accurately, that bread meant for children (the Jews), shouldn’t be given to dogs (the foreigners). She responds that even the dogs gather the scraps from under the table where the children eat. Knocking on doors with a empty stomach I would remind myself that. Even the dogs eat the crumbs. To be honest, I don’t know exactly what all I hope the Catholic Church and Christianity in general will share with me. But I know I was under the table for a long time. I did my best to eat what was given to me, wherever it led. But like that woman in scripture, I am coming on behalf of someone else now. I don’t have any children of my own, but there are millions of kids within and influenced by the teachings of the Church. To the parents and the pastors, the siblings and the strangers, will you share what you’ve got? Because what falls to the floor, I can say from my own life, it does not sustain. At your table you have something better than the inherently disordered shame and silence and loneliness off which we have been trying to survive. Will you share dignity? Will you share love? Will you share marriage? Because you can. Keep us alive. Just because you can.

https://medium.com/reaching-out/gay-and-catholic-30f7755a4726

['Patrick Flores']

2018-12-19 00:33:55.750000+00:00

['Life', 'Storytelling', 'Faithfullylgbt', 'LGBTQ', 'Writing']

The Global Support Ecosystem for Women Entrepreneurs and Investors

The Global Support Ecosystem for Women Entrepreneurs and Investors 340+ VCs, accelerators, angel networks, conferences, platforms, and communities supporting women innovators and investors Changelog: Last updated September 6, 2020 (+AIM-HI Accelerator Fund’s Women’s Venture Competition, Capital Access Lab by Kauffman Foundation, Chingona Ventures, Collab Capital, Diversity Rider Initiative by Act One Ventures, Diversity Innovation Hub, Dreamers & Doers, Firstboard.io, For Colored Girls Who Tech, Hadean Ventures, Hello Career Guru, Included VC, Ingressive Capital, Metrodora Ventures, OSEA Angel Investors, PledgeLA Summer Lab Fund, Startup-Investor Matching Tool, The Community Fund, The Venture Collective, Transparent Collective, WLOUNGE, -The Ventura); July 7, 2020 (+ 24 Hour Assembly, Anthemis, Array VC, Beta Boom, Consider Something Better, Eleanor Venture, Female Innovators Lab, FourthWave, Fund the Women Ventures, Her Corner, Launchpad2x, Lightship Capital, Talent x Opportunity Fund, Venture Forward, Women Founders Community, YSYS, Zane Venture Fund); June 1, 2020 (+ Daintree Capital, Financial Alliance for Women, Invest for Better, Nia Impact Capital, NNE WIN, OneTech, Teja Ventures, wiseHer, Women’s Innovation Fund Accelerator); May 25, 2020 (+ Bossy Chicago, The Capital Network’s Fellowship for Female Founders, Chooks SA, Code Like a Girl, CoworkHERS, DBL Partners, EllePod, Emerge, FD Global’s ScaleUP Programs, Found & Flourish, Girl Geek Academy, H Ventures, Halo Incubator, Heads Over Heels, Her Capital, How Women Invest, Impulse4women, Mums & Co, Rogue Women, Tech Ready Women Academy, WEConnect International, Wedbush Ventures, WeDemption, Women In Innovation; -SheStarts by Blue Chilli); May 11, 2020 (+ 23 Code Street, Female Founder School, Venturous Counsel, W Fund); May 5, 2020 (+ Camelback Ventures, Diana Capital Partners, Female Founder Collective, Female Ventures, Femstreet Membership, For Colored Girls Who Tech, GUILD Academy, Impact By Women, Impact Engine, Marigold Capital, NY Fashion Tech Lab, Scroobious, Women of Wearables) An original version of this list in 2015 could fit on a single slide… Maintaining this list over the last five years has been a labor of love, and one that has allowed me to witness the exponential growth of this support ecosystem for women that build and invest in early-stage companies. Over the last 12 years as the Vice President of Springboard Enterprises, a global network of women innovators transforming industries, I’ve met the leaders of many of the organizations included in this list and I’m honored to be part of a community of exceptional people that recognize this is not only a valuable mission but a lucrative one: there is big money to be made in finding and funding companies led by diverse teams. Since the last edition of this list there is a significant amount of new funding in the hands of women, including funds that do and don’t focus on investing in women-led teams. I love how Jane VC’s Ann Bordetsky put this in a recent post on women-led VC funds: “The most exciting and transformative trend happening in the Tech community right now is a new generation of venture funds — founded, raised and led by experienced, badass women. This wave of Wonder Women will reshape Silicon Valley as we know it.” COVID-19 is also reshaping the startup world and the way that all of us connect with and support those on the herculean mission to build a viable business. Communities are convening in new, virtual ways and evolving their support models. In the coming months, I will update this post to call out those organizations with virtual engagement opportunities. If you’re part of a woman-led company, I hope this list makes your life easier by pointing you to valuable virtual resources and human capital you didn’t already know about.

https://medium.com/been-there-run-that/the-global-support-ecosystem-for-women-entrepreneurs-and-investors-961b3abc2c9b

['Joshua Henderson']

2020-09-06 21:39:43.301000+00:00

['Entrepreneurship', 'Startup', 'Venture Capitalist', 'Venture Capital', 'Founders']

I Can’t BEAR to be Alone: Our Wholesale Fear of Our Own Thoughts

Photo by Anthony Tran on Unsplash In a remarkable study by the British Psychological Society which revealed a great deal about Western society (https://digest.bps.org.uk/2018/10/12/what-are-we-like-10-psychology-findings-that-reveal-the-worst-of-human-nature)/, I read the following: We would rather electrocute ourselves than spend time in our own thoughts Maybe if we spent a little more time in contemplation we would not be so blinkered. Sadly, for many of us, it seems the prospect of spending time in our own thoughts is so anathema we’d actually rather electrocute ourselves. This was demonstrated dramatically in a 2014 study in which 67 per cent of male participants and 25 per cent of female participants opted to give themselves unpleasant electric shocks rather than spend 15 minutes in peaceful contemplation. Although others questioned the interpretation of the results, at least one other study has shown people’s preference for electrocuting themselves over monotony, and another found cross-cultural evidence for people’s greater enjoyment of doing some activity alone rather than merely thinking (also replicated here). The gist of these findings would seem to back up the verdict of the French philosopher Blaise Pascal who stated that “All of man’s troubles come from his inability to sit quietly in a room by himself”. When I was the in the Army, somewhere around 1975 there was a huge popular movement- pushed in part by the Beatles- to learn Transcendental Meditation. The Beatles had gone to study under the tutelage of the Maharisihi Mahesh Yogi. What followed was a great wave of popularity. I was recovering from a series of rapes by a senior officer, was trapped in an ugly and abusive relationship (those things tend to follow one another) and the promise of some mental peace was hugely attractive. I took the course. Got trained. Forty-three years later I can still drop myself off into very deep meditation in a matter of seconds. The result is that I feel as though I’ve had eight hours of sleep. It’s one hell of a life skill. It wasn’t a fix-all. However learning how to meditate has been one of those intensely important skills that the great masters have taught as fundamental to our quality of life. Yet this study points out that most of us in our Western world cannot bear to be alone, much less alone with our own thoughts. While I understand how so many of us seek to drown out our sadness, our angst with noise, entertainment and compulsive shopping (hey, it’s December), I can’t help but wonder at the cost. Photo by Jonathan Bowers on Unsplash Growing up on a farm in Florida, one of the gifts was that we were surrounded by woods. A lake bordered the property. Back in the 1960s as I was just growing up, we had no air conditioning. When we had summer storms, the night was filled with tree frogs and every croaking, singing thing. It was a symphony. Those of us who grew up with the sounds of Nature also tend to appreciate her silence, but also the song that lies within it. Nature’s silence is like a great curtain of calm. Nowhere have I felt this so powerfully than in Iceland. Driving around the Ring Road, there were times that I pulled off the side of the highway, surrounded by high rolling hills. Every so often a sheep would approach, then run. No other cars passed me for hours on end. I would simply stand in the cool, sometimes the mist, and breathe in the vastness of the landscape. Photo by Seth Macey on Unsplash There is an intensity to such silence, a feeling of great portents and promise. That kind of quiet is woven with hope, with grace, and the possibility to reflect upon ourselves, our lives, and what there is to be experienced. Silence speaks to us. Our brains actually grow more cells in the presence of silence (https://www.lifehack.org/377243/science-says-silence-much-more-important-our-brains-than-thought). We heal when we learn to listen to nothing, and release all our thoughts, worries, concerns and -let’s face it- largely meaningless human bullshit to the greater Forces that touch us. Trip Advisor Some years ago I was in South Africa, in the Hluhluwe–Imfolozi Park. The oldest preserve on the continent, you can take your rental car (at your own risk, thank you) through the park, and view all the animals up close and personal. There’s a good-sized hill in the park, the only place it’s safe to get out of your car. On two occasions over the course of the years, I’ve driven to that lookout point to stand and view the animals, feel the wind and drink the African spices deeply into my lungs. I have spoken to what I experience as the Universe, as God, whatever She or He may be. I’ve given myself up to those silences and the beauty of my surroundings. That kind of silence heals. You can release your petty, meaningless bullshit to vastly larger Forces, and be renewed, reinforced and revalued when humbled in the face of All of Creation. When you and I can come to the realization of our meaninglessness, our nothingness, at that moment we can begin to do great work. It’s only in the letting go of our attachments to the ego-based desires that drive our basest selves that we can find true freedom. When I can release my grasping, my neediness ( I wanna be a thought leader!!! I wanna be famous!!!! I wanna be rich!!!! Nobody gives a shit, thank you), then the world opens up like a spring blossom in front of me. If you’re short on examples, witness Nelson Mandela. For years in the silence of his cell in South Africa, this profoundly great man learned to be in his own space. Fill it with forgiveness, wisdom, and the fullness of his being. His ability to be with his own thoughts gave the world one of its greatest leaders and statesmen. You don’t earn that through comfort. You earn that through intensely difficult personal effort.(https://www.today.com/popculture/prison-was-mandela-s-greatest-teacher-wbna36087300) Silence is one of our greatest teachers. In the face of silence, Nature’s great healer, we come to know our sacredness. Photo by Greg Rakozy on Unsplash While vastly too many of us fear what we think, the truth is that in the heart of silence we can come to know that spark of Creation that exists in all of us. That animates us, gives us movement. Gives us wings, should we choose. Rather than experience silence as terrifying, which our Western society uses to sell us stupid shit like all manner of devices which distract, damage, ruin our hearing and invade everyone else’s quiet space, the soft cushions of our inner world, the quality of our own thinking (or lack thereof) provide a training ground. In his magnificent book The Heart of the Buddha’s Teaching, the great Vietnamese monk Thich Nhat Hanh writes that our emotions are like a great river. We can sit quietly on the bank and watch them flow by. Recognize each as they arise. “Ah,” we can say. “I am feeling anger.” “I am feeling sadness.” We can hold these mercurial feelings in our hands, and let them touch us deeply. We validate, feel, and honor our emotions, as valid aspects of our humanness. Then they can flow on. What we resist, persists. What we fear, we store inside us like a cancer. By allowing, those feelings, which we fear so deeply, can simply be, then pass, like so much morning fog. For most of us, emotions are terrifying. Our sadness, our despair, our anger overwhelm us. It is far more common to want to medicate, deny or avoid our feelings completely, when to honor them allows us to recognize their sources. When we do that we can see if there is a place of suffering. Often in the study of the feeling we see the seeds of our release, whether it’s an attachment to a thing, a person, a way of being, or simply a feeling that flits through us the way a swallowtail butterfly delicately flutters through a garden. ButterfliesatHome.com The ability to allow the flow from our hearts is one of the secrets of peace. Everything we feel is valid. When we honor, experience and move through those feelings we learn to touch the outer boundaries of the self. This allows us to know ourselves, then push that boundary outward. Each time we allow our feelings, we build the strength to trust that they won’t overwhelm us. Our tendency is to want to control our feelings. That forces them to go underground and explode later in a spectacular display worthy of Yellowstone. And wholly unnecessary. We fear being overwhelmed by our feelings. This is one of the drivers of the opioid epidemic, most certainly behind much of alcoholism and all the other addictions that serve as perfect distractions to the richness of our human experience. As long as we are in the throes of some kind of addiction, we don’t have to face the Self. And yet, sitting with the Self in the quiet of our hearts, we find little to fear. Little to be threatened by. Puff the Magic Dragon indeed. Photo by Tarik Haiga on Unsplash Peace- what so many say that they want- is available right here, right now, always and forever. It is borne of being able to be deeply inside the Self, leaning thoughtfully against the bedrock of the soul, that immutable and forever part of us that is expressed as the Kingdom Within. There is much to trust there, but when we don’t explore the quiet reaches of our hearts and souls, it’s easy to believe that darkness is full of monsters. The quiet of our inner space is as vast as the Universe itself. On a quiet, lonely beach in Eastern Madagascar, three hours by horse east of Brickaville (which is eight hours by car from the capital), I spent a week in silence. The early mornings were spent horse backriding from 5:30 to 9:30. Then, giving the horses over to the staff for a dip in the channel, I took up a spot against the brick building which was our baseops. No electricity. No running water. Most everyone spoke French or Malagasy. Perfect. Dawn on a Madagascar beach From 10 am until I went to bed at sundown, I had the beach to myself. The only sounds were the breakers on the beach just over a grassy hill, the songs of birds as they constructed nests in the nearby palm trees. The quiet, gentle breathing of the two strays which I had adopted for the week. The onshore winds which made the heat bearable. In an increasingly loud world where even the whales can’t communicate due to the noise (https://www.theguardian.com/environment/2016/feb/02/ships-noise-is-serious-problem-for-killer-whales-and-dolphins-report-finds), it’s hard for any of us- human, animal, insect, the like- to find our place in the industrialized world. There is no peace in man-made noise (and I don’t include music in this, although some types, let’s be clear, are bad enough to make anyone want to sail to the Hebrides forever). There is peace in Nature, in her sacred silences, and in the perfect music she creates. We are tearing more and more of that down, burning it and destroying it even as we increasingly, desperately need it. Photo by Jared Rice on Unsplash If silence scares you, that’s an invitation. In the perfect quiet of a deep forest — quiet for lack of someone’s playlist, their incessant chatter, the noise of cars and planes and ATVs — we have the opportunity to find peace. The truth of why we are here. What makes us human, and what makes us part of the larger movement of life on this planet. The more we isolate ourselves from Nature, the more we fear Her. And yet, in her embrace, lie more answers than questions. No matter where you go, where you move, no matter where you travel, peace will always and forever elude you if you don’t go within. While finding a spot of nature is hugely helpful, the blessed peace and solace that so many of us so desperately want is forever abiding inside us. There is quiet. There is peace. The cathedral of the soul always has a seat for us, if we’re willing to sit down in the perfect quiet of the heart.

https://jhubbel.medium.com/i-cant-bear-to-be-alone-our-wholesale-fear-of-our-own-thoughts-103309e641f1

['Julia E Hubbel']

2018-12-07 13:03:49.963000+00:00

['Self-awareness', 'Self Improvement', 'Life Lessons', 'Wellness', 'Meditation']

How To Make The Coronavirus Work For You

Are you afraid or experiencing financial hardship during the coronavirus spread like I am? I can honestly say it gives me more of a reason to make my resume perfect, and it gives me the time to get the certification I’ve been wanting to further my career with. I can assure you, this is the perfect time to start doing the things you put off because you were too busy. There are just so many things I can do to make this obstacle into the life raft I need to get ahead in the world. This coronavirus is trying to split communities apart. It’s making people afraid to be be within 6 feet of each other. Maybe it’s time we start thinking of ways to communicate and feel that bond while still being quarantined. It is definitely possible with the technology we have today. When was the last time you wrote a nice letter to someone? We have email now! Or the “Marco Polo” app(not a sponsor), or called someone? Tell people what you are working on, what you’re grateful for. The other day I called a friend up and just chatted with him for over an hour about nothing in particular, and felt a deep sense of friendship once the call ended. The kind I felt with him when we lived by each other and worked together. I haven’t felt that close of a bond with him in 7 years. Now I feel like calling all of my friends and just seeing how they are doing. It feels good. Social media is a great way to connect but it’s also very intrusive and has built distrust within our social circles and communities. With all the companies spying on our psychological patterns and how we use social media, I understand why some of the older generation are wary to trust these corporations. I am the first one to say social media is not the healthiest way to communicate. But a time like this calls for thinking outside of that explanation and expand our communities through knowledge in the social media realm. Instead of fearing it, get to understand it and create your boundaries around it. Now is the time to pick up that phone and strengthen a bond with an old friend. The impediment of self-quarantine is no reason to stop your life, it’s more reason to begin a new life. One where you do what you love to do as your work, that skill you dreamed of doing when you were a teenager, but instead chose a safer path. Create stronger bonds of friendship through the use of modern technology. Italians have been singing together and to each other. Their Air Force even put on a show for them to bring entertainment to their lives. When was the last time you got excited about seeing planes fly in the sky, I can surely say it’s been a long time for me. And maybe sooner rather than later we will all understand what that ancient roman meant when he said:

https://medium.com/modernmeraki/how-to-make-the-coronavirus-work-for-you-3f5635d9f155

[]

2020-04-22 19:39:59.812000+00:00

['Self Improvement', 'Mental Health', 'Covid-19', 'Coronavirus', 'Philosophy']

How to Go No-Contact After a Breakup

Every heartbreak hurts. Every break up will shatter you in some way. But there’s nothing more heart-wrenching than surviving after a relationship with a narcissist. There exists a whole range of toxic people out there, ranging from energy vampires, average jerks, selfish and entitled individuals and, right at the other end of the scale, narcissists, psychopaths and sociopaths. They are all dangerous and detrimental to your mental and emotional health. Relationships with such people are inevitably going to end — and either when you are breaking up with them, or when they discard you for the umpteenth time and you finally say it was enough. That’s when no contact comes into play. Originally the no contact rule was made up by dating coaches who suggested no contact as a means of getting back with your ex. As if manipulating someone into wanting to be with you after they left you would really be a viable option for most of us. As if something utterly broken could be repaired by playing hot and cold. I’m not saying it never works — some might need a wake-up call to realise how much they lost. But in most cases, it’s doesn’t. No matter what kind of ideology or pseudo-science you put behind it, it’s still manipulation and it doesn’t work. It just not how it should be. There is usually a good reason that a relationship goes south, and in most cases, the breakup comes after you tried to solve your problems in a mature way. In this case, manipulation is not the answer. But no contact shouldn’t be about manipulation. It is about self-preservation and survival, and it’s not selfish, but a necessary act.

https://medium.com/mind-cafe/how-to-go-no-contact-after-a-breakup-642523f110b7

['Zita Fontaine']

2020-01-23 17:21:43.158000+00:00

['Relationships', 'Self', 'Mental Health', 'Love', 'Psychology']

How to create complex folder structures with just 1 click

Why you should proceed or not proceed reading this article: Even if the next general principles could be applied to any folder structure on any digital support you are using, I unfortunately still don’t know how to create all the automations and the amazing hacks that the built-in Apple native app iOS Shortcuts are giving even to non programmers users. All my articles and the tools I provide are always meant and thought to respect your precious time. So if you are an Android or Windows Phone OS user I greatly respect you but I don’t want you to invest even a minute going on unless you are interested on giving a quick glance on what’s possible to do on iOS devices with little or no experience at all. But if you are an Apple user you will find in the next few lines all the basics to create your own “1-click automated folder creation tool” and at the end of this article I will also provide a screen recording of the Shortcut in action and a link to a ready-to-go Video Creation Nested Folder Structure Shortcut that you can download and use as-is or even adapt it to your specific needs. Anyone who is reading this, one day or another, probably has stumbled upon the same question that any content creator, whether is making videos or reportages, recording podcast, writing articles or books, giving courses, public speeches or just a simple presentation, has to confront: “Where did I saved that piece of information, that note, that picture, that footage, that audio, that #*%’ (fill at your will!) I am now getting so mad at finding out again?” Don’t break the flow while you are in “the zone”! When you are planning or drafting your content, if you are somewhat like me, you are probably ending up with multiple browser tabs opened, many links, notes, pictures and contents that you have set apart to help you craft your next creation. Even for relatively simple video content, the resources scenario could evolve so complex and intricate that without you are even realizing, it really could be too late to fix the structure; you will probably end up cluelessly scratching your head and wasting your time (and sometimes your patience too!) trying to figure out where you have put that missing piece of content that keeps you stuck. Courtesy of https://unsplash.com/@karinacarvalho You maybe have your B-rolls on a SD card, other footage on a local drive, some templates or general resources on Dropbox or iCloud, the audio or the voiceovers on your recorder, the music on different online services, the outline on a Google Doc or in Notes, some useful links in Evernote, pictures in the Image folder, and if you use mindmaps or even storyboards, you could have sketched them somewhere on your iPad. I don’t know about you, but I used to really get annoyed and frustrated when I was in the middle of “The Zone” and I suddenly get stuck because I wasn’t able to immediately find that single missing piece to proceed at full steam ahead. And sometimes when I get back from the “M.I.A. rescue recovery mission” I found myself having lost all the momentum; getting back to the creation or the editing part had become so hard that I eventually decided to stop and resume the work in a different moment. Structure your resources before you start your next project! If you are a professional content creator working everyday on multiple projects at the same time, I am quite sure that you have adopted the following tactics a long time ago, so probably you could skip this section without any worries. But if you’re an occasional content creator just like me this simple strategy could really save you a lot of time and frustration waiting you down the road! “ Please do your future self a real favor! “ Resist the temptation to dive-in immediately on the creative part for your next project and give this simple solution a try. I’m quite sure that you will heartfully thank yourself as I have already done not a long time ago. (Today! …as I am writing this) Any real professional crafter (a cook, a painter, a craftsman, a mechanic,...you name it!) knows that the working place and the setup has to be made upfront the starting of the works and that it will be infinitely easier and better if you prepare your tools and all the “ingredients” of your recipe (or anything you will possibly need) in advance. Speaking about content creation, anytime I start a new project, even for something like this article, I fire a very simple but really powerful iOS Shortcut that immediately creates inside iCloud a well organized nested folder structure that I will use to store anything that could relate to that specific project. Courtesy of https://unsplash.com/@barnimages I have invested a few minutes to plan and figure out what will be the ideal folder structure for any kind of project that involves resources; then I decided a specific and predetermined location for everything that I am sure I will later remember and also get used to, for whatever I will needed further down in the workflow. So now, anytime I need for example to store B-Rolls footage, or screenshots for a tutorial, or adding content to an article outline, or storing an audio recording, I am sure that I already had setup in place the right and organized containers to store them without the risk of puzzling and mixing too much. Whenever I am starting something new, having this preset Master Folder let me easily move it inside or outside of the filesystem or even from the device; I could also put it in shared cloud collaborative storage like Google Drive or Dropbox to easily get outside contributions while collecting all the raw materials. The beneficial side effect of this simple strategy is that for every project you complete you are building some kind of “muscle memory” so when you gather together the various pieces and decide to store something, or anytime you need a piece of content, you already exactly know where it belongs and where you will find it later on. Did you know you had the Ultimate Toolbox inside your iOS device? For all the relevant information explaining what iOS Shortcuts are and how to use them you can refer to this Apple website section. Just to put it down in really simple words, think about them as a full LEGO set: you have multiple pieces each with specific functions and outputs (these building blocks are called Actions) that you can combine, pile up and put together to execute a set of instructions, to manipulate a wide variety of contents or inputs, to choose between different options and so on. Courtesy of https://unsplash.com/@krstne And these combinations and possibilities are nearly infinite and extremely customizable for any of your specific need. It’s like the Genie in The Bottle: you can quite really get whatever you want from your iOS device and, with the right knowledge and experience, even build your own apps and your automations that can go across almost the entire Apple devices ecosystem and that are fully integrated with Siri. How to create nested folder structure with iOS: This is how simple is to use the Shortcut: You trigger it with voice control by saying out loud the Shortcut name after the “Hey Siri” or clicking on its tile-like button. (It can also be triggered automatically by other Shortcuts if it’s part of a chained or a multiple steps workflow!) You are prompted to choose the name of the Project that will be your new Master Folder. In one fraction of second it goes through the set of actions and it creates in iCloud/Shortcuts/ the structured nested folder you have planned. It notifies you that it successfully created a new project folder and it asks you to choose between opening the Files app or simply exiting with a Notification. It’s done: you don’t even have to think about it more.

https://medium.com/swlh/how-to-create-complex-folder-structures-with-just-1-click-47f6909b86b4

['Giacomo Pasini']

2020-05-17 17:34:04.630000+00:00

['Apple', 'Automation', 'Shortcuts', 'Productivity', 'Filmmaking']

Please motivate your team, but responsibly

Years ago, I was devastated when a project I had poured so much passion into was one day unceremoniously cancelled. It hurt. And what was worse was I had encouraged my team to also emotionally invest themselves. I learned many lessons from that experience. I vowed never to put myself or anyone else in such a vulnerable emotional state again. Work was not worth it. Now I’m starting to rethinking that approach. In the office, we are encouraged to take a rational, not passionate approach to our daily tasks. Emotions are for the home, especially undesirable ones like anger, jealousy, or stress. The idea of having a version of yourself for work and another for the home has somehow become an internalised trait for the office worker. Nobody has told us to do this, so why do we lean into it? It’s not like the underlying characteristics of my professional conduct a.k.a. being a decent human being, ends at 6 PM. I can only assume it’s a kind of defensive mechanism — a way of conserving mental energy for rigours outside of working hours. Why should you get excited about a project? It could fail or end for reasons outside your control. Who needs that drama in their lives? Well …. I think you do. The Inspiration ’Trick’ Enter the product manager. You find a problem, validate a hypothesis, test a solution, measure the impact, and repeat. No matter how emotionally unattached and objective a decision-maker, you think you are, you are slowly falling into an emotional trap. With each successive choice made, you are directly and indirectly tying the product's fate with your own. It becomes the most visual representation of your taste and judgement. Now, this not necessarily a bad thing from my perspective. This means you have ‘skin in the game’ and should hopefully exercise a more considered strategy to improve your outcomes. The trick becomes knowing when that emotional component is more harmful than helpful. Inspiration is an excellent example of this. People like to be inspired. It boosts productivity, stimulates creativity, and most importantly makes work worth waking up for. Enough inspiration can even distort the way you see the world into something where anything seems possible. The “Reality Distortion Field” is a term first used to describe this effect based on observations of Steve Jobs’s management style. Jobs’ could convince himself, and others around him, to believe almost anything with a mix of charm, charisma, bravado, hyperbole, marketing, appeasement, and persistence. Great for motivation, but was also likely the source of much unnecessary misery when asked to achieve the impossible. You need to take responsibility for the optimistic feelings you are leading others towards. Inspiration can be a potent productivity trick, but knowingly abusing it is an act of psychological sabotage. Don’t misguide people, don’t overstate rewards, don’t promise things you can’t deliver, and be realistic with problems you encounter. Inspiration and optimism are like wind in the sails of any new idea. With the promise of treasure and riches you put together a crew, a ship, and set out on murky waters. When you take the first step on the journey of a thousand miles, it looks like a long way, and it really helps if someone is saying “We’re one step closer.”, “I promise it’s not just the siren songs and jagged rocks out there”. Being the keeper and reiterator of the vision takes considerable will power and even self-delusion. If someone decides to invest their emotional energy in your vision, you better make sure you are making the best strategic decisions possible. Don’t be deceptive. Another risk is becoming so enamoured in your own passion that it blinds you to the reality of the situation. The trick is not to let your own desires completely blind you to the faults behind an idea or perspective, nor allow those same shortcomings to impact your team. Leveraging Emotion for the Unemotional But, I understand leading by emotion is not for everyone. If you need to conserve energy and employ pragmatism to get the job done then fine. Try the following instead. When describing your vision, by all means, make sure its purpose is practical, but be careful not to make it completely logical. Make its purpose of a sentimental or emotional type. A logical problem, for example, is designing a “Sign In” experience and getting a visitor into their account. But emotionally, consider how frustrated you were that time when you couldn’t log in to a site you really needed. You wouldn’t wish that experience on anyone else, right? Build your product vision around minimising those kinds of feelings. The Dark Side of Passion What do you do when all this emotional investment brings out your worst characteristics? Resilience can take you far, but bad days will come, and anger, jealousy, and stress will raise their ugly heads. Our commitment to passion makes us vulnerable to these feelings. A single lousy episode can be enough to untangle a year’s worth of camaraderie. It’s wise to bear in mind that your teammates may not remember the excellent work they produced, but they will certainly remember how poorly you behaved under pressure. To prevent this, we need to be actively conscious of our emotional state and leverage compassion to rein it in. Anyone who has been in a meeting filled with passionate voices knows what I’m talking about. You need to take a second, step back, consider the perspective of the person across from you, then respond. What I’m discovering is we need to build a system of thinking that intentionally forces us to slow down. Take the time to mull over feelings and absorb a greater variety of logical pieces. It’s at high emotional points (both good and bad) when we should stop and reflect before making the next move.

https://uxdesign.cc/please-motivate-your-team-but-responsibly-b81db34791fb

['Adrian H. Raudaschl']

2020-11-27 11:28:39.904000+00:00

['Product Management', 'User Experience', 'Psychology', 'Productivity', 'Product Design']

The Myth of the Boiling Frog

How gradual change goes unnoticed until it’s far too late. The idea goes like this: If you put a frog in boiling water, it will jump out. But if you put it in lukewarm water and gradually increase the temperature, it won’t notice and it will be cooked alive. While this, of course, isn’t actually true, it paints a useful picture that feels far too familiar… And is rather disconcerting. For it appears to be a common view — that the world around us is changing at an exponential rate — technologically, culturally, and politically. As it seems to begin with scientific development (and rightly so), which then becomes technological innovation, which in turn affects us culturally, and finally leads to sudden political shifts, which would have been considered outrageous just barely a decade ago. And, in fact, many of them were. Just as many more are today — at what seems to be an ever increasing pace. But imagine this —have the so called ‘outrage’ or perhaps even ‘cancel’ culture been an inevitable, natural development? If you’ve ever thought about the internet as a concept, then I expect your answer would be ‘yes’. After all, neither the concepts of ‘outrage’, nor ‘cancelling’ are particularly new or unfamiliar to history, and yet, either they suddenly became popular, or we suddenly felt that the water is hot. And if you break down what the internet actually is in simple terms — a method for near-instantaneous, world-wide communication that currently, more than half the human population is taking part in — you get your answer. It’s both. We were ‘suddenly’ given a platform to voice our thoughts, feelings, opinions, and analyses… And we could ‘suddenly’ see and hear everyone else’s, too. But this, of course, wasn’t the case before the so-called ‘social media’ became prevalent… Which are what, exactly? …An inevitable development of the internet, just as the internet is an inevitable development of computing. And all of this was preceded by television and radio — except, you might say, that those methods of communication were not available for everyone to take part in… Perhaps you could be right. …Except that, in reality, all that’s different about them is that the internet has simply become cheaper and more efficient at transmitting information. After all, once you have a device and a connection, communication is practically free. The cost is in building and maintaining the infrastructure — not in sending the message. As technology becomes more potent and efficient, it increases our capacity to develop more potent and efficient versions of itself. And so, we end up witnessing the world pass us by, often without having time to think, say, or do anything about it. It is almost as if the conditions for the development of an Artificial Super-intelligence were set in motion by the very development of human consciousness… Which, in turn, was set in motion by the very development of life on Earth. And if that’s the case… Then what this means is that the idea of a technological singularity would also have been set in motion by those exact same events. In other words, it is entirely possible that the path on which we are headed is, in fact, an inevitable consequence of evolution — that the ‘telos’ or ‘natural end’ of biological life is… Machine life. Just as living beings are composed of things which are not ‘living’, and consciousness is composed of things which are not ‘conscious’, so would mechanical life be composed of things which are neither ‘mechanical’, nor ‘alive’. A human-machine symbiote… Which is precisely what humanity has always been — a monkey with a spear, a monkey with a gun. A monkey with a screen, a monkey with the power of the sun. And it is also to no surprise, that just as all previous methods of communication would regulate their content, and therefore censor what would jeopardise their broadcasting — so too would social media companies. Except, that this time, nearly everyone is part of it, meaning that to censor is to exile — and to support is to sanction. It is certainly the case that many of these companies already have enough power and influence that they could be listed as small nations. And at this point, there is nothing that can be done about it. The water is already boiling hot. What’s more, it is not that this ‘could not have been foreseen’ — it probably was by some — but rather, that it simply could not have been otherwise. The very end goal of the internet is to digitize our lives… Entirely. For if it can be digitized — it will be digitized. Since the advantages are overwhelming, and the disadvantages are sentimental at best — what will transpire is the complete digitization of the human mind. And when it comes to our bodies, the same trend will continue as it always has — we will simply neglect them, until we finally leave them behind. But there is nothing to lament here. There is nothing lost, and nothing gained. It is merely the nature of humanity emerging in the shape of its own creation. Some are beginning to realise where we are headed, and in their panic ask us to turn back. Others are staring far into a void, and cynically dismissing the reality of our own condition. But make no mistake — it is a deeply human condition. And if you ask at what point the water was too hot, the answer is… It was boiling much before we jumped into the pond.

https://medium.com/carre4/the-myth-of-the-boiling-frog-dc2e9427bd7b

['Stan Daskalov']

2020-10-27 12:24:12.330000+00:00

['Technology', 'Artificial Intelligence', 'Life', 'Psychology', 'Philosophy']

Apache Airflow: A Real-life Use Case

Overview Airflow is simply a tool for us to programmatically schedule and monitor our workflows. When dealing with complicate pipelines, in which many parts depend on each other, using Airflow can help us to write a clean scheduler in Python along with WebUI to visualize pipelines, monitor progress and troubleshoot issues when needed. Real-life Example The best way to comprehend the power of Airflow is to write a simple pipeline scheduler. A common use case for Airflow is to periodically check current file directories and run bash jobs based on those directories. In this post, I will write an Airflow scheduler that checks HDFS directories and run simple bash jobs according to the existing HDFS files. The high-level pipeline can be illustrated as below: Pipeline Overview As you can see, first we will try to check the today dir1 and dir2, if one of them does not exist (due to some failed jobs, corrupted data…) we will get the yesterday directory. We also have a rule for job2 and job3, they are dependent on job1. So if job1 fails, the expected outcome is that both job2 and job3 should also fail. This is one of the common pipeline pattern that can be easily done when using Airflow. Setting Up There are a lot of good source for Airflow installation and troubleshooting. Here, I just briefly show you how to set up Airflow on your local machine. Installing Airflow using pip: pip install apache-airflow Initialize Airflow database: airflow initdb Start the webserver: airflow webserver -p 8080 Run the scheduler: airflow scheduler If all run successfully, you can check out Airflow UI via: http://localhost:8080/ OK, let’s write it! First we need to define a set of default parameters that our pipeline will use. Since our pipeline needs to check directory 1 and directory 2 we also need to specify those variables. Fortunately, Airflow leverages the power of Jinja Templating and provides the pipeline author with a set of built-in parameters and macros. Airflow also provides hooks for the pipeline author to define their own parameters, macros and templates. This is how we define it: Define default parameters Here is the brief description for each parameter: owner: Owner of the pipeline, this will be shown on the webUI. Owner of the pipeline, this will be shown on the webUI. depends_on_past: Whether or not this pipeline will be dependent on the past pipeline instance. So if your past pipeline had failed, this current pipeline will not be triggered. Whether or not this pipeline will be dependent on the past pipeline instance. So if your past pipeline had failed, this current pipeline will not be triggered. start_date: The start date of your pipeline. The start date of your pipeline. email: The email to notify. The email to notify. email_on_failure: Specify the email that will be notified when your pipeline fails. Specify the email that will be notified when your pipeline fails. email_on_retry: Whether or not to notify email when retries. Whether or not to notify email when retries. retries: Number of retries. Number of retries. catchup_by_default: Whether or not to run the all previous scheduled pipelines if you start date is from the past. Whether or not to run the all previous scheduled pipelines if you start date is from the past. params: User-defined parameters for this pipeline, this will be accessed by Jinja template {{ params.my_param }}. As for build_params functions, this function just loads the user-defined variable from yml file. This is a good practice to load variables from yml file: Read user-defined variables from yml file Since we need to decide whether to use the today directory or yesterday directory, we need to specify two variables (one for yesterday, one for today) for each directory. The yml file for the function to load from is simple: yml file After specifying the default parameters, we create our pipeline instance to schedule our tasks. In Airflow terminology, we call it DAG: A DAG – or a Directed Acyclic Graph – is a collection of all the tasks you want to run, organized in a way that reflects their relationships and dependencies. This is how we define it: Define DAG Here we want to schedule the DAG to run daily by using schedule_interval parameter. Next we write how each of the job will be executed. Specifically, we want to write 2 bash jobs to check the HDFS directories and 3 bash jobs to run job1, job2 and job3. Here, the bash jobs are just simple commands but we can arbitrarily create more complicated jobs: Bash job functions Since we want to pass the checked directories to job1, we need some way to cross-communicate between operators. Luckily, Airflow does provide us feature for operator cross-communication, which is called XCom: XComs let tasks exchange messages, allowing more nuanced forms of control and shared state. The name is an abbreviation of “cross-communication”. XComs are principally defined by a key, value, and timestamp, but also track attributes like the task/DAG that created the XCom and when it should become visible. Any object that can be pickled can be used as an XCom value, so users should make sure to use objects of appropriate size. Here in check_dir1 and check_dir2 functions, we echo the directories for job1, we can get those directories by using this Jinja syntax: {{ ti.xcom_pull(task_ids='Your task ID here') }} The last thing we need to do is to instantiate airflow jobs and specify the order and dependency for each job: The syntax [A, B] >> C means that C will need to wait for A and B to finish before running. Another way you can write this is to use set_downstream function: A.set_downstream(B) means that A needs to finish before B can run. Each of the bash job instance has a trigger rule, which specifies a condition required for this job to run, in this code we use 2 types of trigger rule: all_done: All previous operations have finished working no matter they are successful or not. All previous operations have finished working no matter they are successful or not. all_success: All previous operations have finished successfully. After you have created the whole pipeline, all you need to do is just start this scheduler: python scheduler_demo.py Note: The default DAG directory is ~/airflow/dags/. So all of your code should be in this folder. You need to wait a couple of minutes and then log into http://localhost:8080/ to see your scheduler pipeline: Airflow UI You can manually trigger the DAG by clicking the play icon. You can also monitor your scheduler process, just click on one of the circles in the DAG Runs section: Click DAG Runs section After clicking on a process in DAG Runs, the pipeline process will appear: Scheduler process This indicates that the whole pipeline has successfully run. This is how you can create a simple Airflow pipeline scheduler. The whole script can be found in this repo. Thank you for reading till the end, this is my first post in Medium, so any feedback is welcome!

https://medium.com/analytics-vidhya/apache-airflow-a-real-life-use-case-faf3b2439e86

['Bào Bùi']

2019-09-06 04:24:21.555000+00:00

['Airflow', 'Python', 'Data Science', 'Data Engineer', 'Big Data']

Listening With Curiosity

Photo by Amy Hirschi on Unsplash What is a Good Listener? A good listener is someone who doesn’t talk over the other person. They are patient and pause in between sentences to allow others to speak. They address people by their names and make eye contact with them. In May, I wrote an article called Talk Less, Say More where I talked about why you should invite others to share their perspectives with you. After all, people tend to be more attracted to those with good listening skills. What I didn’t talk about were the techniques that I use for effective communication and what has helped me become a better listener over the years. If you have any tips you’d like to add, I’d love to hear from you below in the comments. Be Curious About People

https://medium.com/the-partnered-pen/listening-with-curiosity-29389e96bf84

['Katy Velvet']

2019-07-28 22:55:03.523000+00:00

['Leadership', 'Self Improvement', 'Relationships', 'Mental Health', 'Psychology']

當創新創業從傳奇故事變成科學實驗

in In Fitness And In Health

https://medium.com/yiyi-network/startup-as-a-science-409787da9214

[]

2020-04-02 16:32:58.770000+00:00

['Steve Blank', 'Startup', 'Business Model Canvas', 'Customer Development', 'Science']

How to Get Around Newspaper Paywalls in 2020

A paywall is a method of restricting access to content via a paid subscription. Beginning in the mid-2010s, newspapers started implementing paywalls on their websites as a way to increase revenue after years of decline in paid print readership and advertising revenue. In academics, research papers are often subject to a paywall and are available via academic libraries that subscribe. Wikipedia Founder Jimmy Wales has stated that he “would rather write [an opinion piece] where it is going to be read”, declaring that “putting opinion pieces behind paywalls [makes] no sense.” Without easy access to both read and share insights and opinions, the online news platform loses an essential characteristic of democratic exchange. This article is not meant to debate the commodification of information. If you use a news-source regularly for work or personal use, and derive significant value from it, you should pay for it. But in an increasingly fragmented media landscape, it is not economically feasible for a casual reader to pay for a costly monthly or yearly subscription to dozens of news sites. Below is a (nearly) comprehensive guide to the various methods allowing you get around paywalls, pop-ups, and adwalls, that are common on many news sites. There will always be one or two articles that you cannot access without a purchase or compromising your personal information, but you should be able to access at least 95% of news content for free using these tricks. These techniques will help you get around paywalls for the Wall Street Journal, New York Times, Washington Post, Financial Times, and more, without requiring username and password logins credentials or illegal hacking. One last note before you start hacking paywalls. If you only need access to these sites for a brief period of time, you may be better off taking advantage of the free trial periods many publications offer and cancelling your subscription before it renews: Source: Paywall Hacks How to Get Around Almost any Paywall Easily (UPDATED 12/2/19 with new WSJ Bypass) I vowed to find a way around their paywall after they sent a cease and desist to Outline (still an amazing resource for many news sites). It took me a few tries to find something that works, but here you go: 1. Use The Following Firefox Browser Add-on Link: https://github.com/iamadamdev/bypass-paywalls-firefox/blob/master/README.md Note: this add-on reportedly works on these other sites as well (although I have not tested all of them): Baltimore Sun (baltimoresun.com) Barron’s (barrons.com) Bloomberg (bloomberg.com) Caixin (caixinglobal.com) Chemical & Engineering News (cen.acs.org) Central Western Daily (centralwesterndaily.com.au) Chicago Tribune (chicagotribune.com) Crain’s Chicago Business (chicagobusiness.com) Corriere Della Sera (corriere.it) Daily Press (dailypress.com) Denver Post (denverpost.com) De Tijd (tijd.be) de Volkskrant (volkskrant.nl) The Economist (economist.com) Examiner (examiner.com.au) Financial Times (ft.com) Foreign Policy (foreignpolicy.com) Glassdoor (glassdoor.com) Haaretz (haaretz.co.il / haaretz.com) Handelsblatt (handelsblatt.com) Hartford Courant (courant.com) Harvard Business Review (hbr.org) Inc.com (inc.com) Investors Chronicle (investorschronicle.co.uk) Irish Times (irishtimes.com) La Repubblica (repubblica.it) Le Temps (letemps.ch) Los Angeles Times (latimes.com) Medium (medium.com) Medscape (medscape.com) MIT Technology Review (technologyreview.com) Mountain View Voice (mv-voice.com) National Post (nationalpost.com) New Statesman (newstatesman.com) New York Magazine (nymag.com) Nikkei Asian Review (asia.nikkei.com) NRC (nrc.nl) Orange County Register (ocregister.com) Orlando Sentinel (orlandosentinel.com) Palo Alto Online (paloaltoonline.com) Quora (quora.com) SunSentinel (sun-sentinel.com) Tech in Asia (techinasia.com) The Advocate (theadvocate.com.au) The Age (theage.com.au) The Australian (theaustralian.com.au) The Australian Financial Review (afr.com) The Boston Globe (bostonglobe.com) The Globe and Mail (theglobeandmail.com) The Herald (theherald.com.au) The Japan Times (japantimes.co.jp) TheMarker (themarker.com) The Mercury News (mercurynews.com) The Morning Call (mcall.com) The Nation (thenation.com) The New York Times (nytimes.com) The New Yorker (newyorker.com) The News-Gazette (news-gazette.com) The Saturday Paper (thesaturdaypaper.com.au) The Spectator (spectator.co.uk) The Business Journals (bizjournals.com) The Seattle Times (seattletimes.com) The Sydney Morning Herald (smh.com.au) The Telegraph (telegraph.co.uk) The Times (thetimes.co.uk) The Toronto Star (thestar.com) The Washington Post (washingtonpost.com) The Wall Street Journal (wsj.com) Towards Data Science (towardsdatascience.com) Vanity Fair (vanityfair.com) Wired (wired.com) You should see a page like this: If you scroll down, you will see the following: Click the download link. Accept the Firefox permission popups that appear. Customize. You can customize the browser extension. If you have other existing logins, make sure you deselect these news sites as this add-on will log you out of them.

https://medium.com/paywall-hacks/how-to-bypass-virtually-every-news-paywall-705602c4c2ce

['Casey Botticello']

2019-12-30 02:12:51.022000+00:00

['Technology', 'Productivity', 'Entrepreneurship', 'Privacy', 'Social Media']

Shoes and Shirt (and Pants) Required

Shoes and Shirt (and Pants) Required When what we wear affects how we write Photo by NordWood Themes on Unsplash “Put your pants on, and come with me!” In good fun, this is what my father-in-law said he’d say if he ever caught me in bed with his daughter before we got married. Turns out, it’s great advice for writers. In a hobby and profession that lends itself to comfy clothes and couches, sometimes the best advice is to put on an actual pair of pants. Today’s Covid world is getting a taste of the writer’s life. Daily showers, business wear, and shoes are a thing of the past, and in many instances, clothing is optional. All one has to do is turn off the alarm, roll out of bed, and log on. As a measure of professionalism, one’s physical presentation has been replaced with zoom conduct (you’re on mute, you’re still on mute), and if there is video interaction, it’s from the waist up. So while some are still required to be business on top, it’s all casual down below. Admittedly, this is one of the perks of being a writer. Sure, there’s the occasional face to face interview or the rendezvous with your skinny mocha and favorite lounge chair at the local coffee shop. But the majority of writing can be done at home, alone, in your pajamas. And until recently, writers held sway in this corner of the market where quality output came with a clothing optional clause. But at what point does clothing optional start to work against us? I wonder if the haziness we experience in our mind, a bout of writer’s block or lack of inspiration, comes from the idleness we portray on our bodies. Does what we wear and how we present ourselves, even when no one is around, have an effect on the quality of our work? The mind-body connection within the brain is complex. Think about what happens when a person you’re attracted to walks in the room. Your heartbeat ramps up and your breath quickens. Your focus narrows and whatever you were thinking is now in the past. All your mental energy is centered on that one person, and while the world around you may be a blur, you’re also fully present and attentive. This and more from just one look. So that begs the question, what are we telling ourselves as writers when we stay in our pajamas all day? If the interconnectedness of mind and body is such that one affects the other, perhaps the lackadaisical attire of our body is communicating futility to our mind — communicating that it’s not, in fact, time to write. And if we still do so, do we risk not having a fully present, attentive, and focused mind? This not only affects our production rate, but the product itself. Here, though, is where “put your pants on and come with me” stands as a rallying cry for motivation. The simple act of putting on a pair of pants made by someone other than lululemon or Hanes, a clean shirt, and dare I say a pair of shoes, may be the kick start our mind needs to get in gear and focus. With our outward appearance, we’re communicating to our mind the seriousness of what we’re about to do, namely write, and that it needs to take it seriously too. Throughout the day, every look down or glance in the mirror at our body reinforces this seriousness to our mind. And just like looking at the person we’re attracted to, our whole self becomes present, providing the focus we need for the task in front of us. I’ll admit that putting on a proper outfit when I know I won’t be seeing anyone feels silly. Add to that a pair of shoes or boots while just sitting around the house, and it seems comical. Especially when comfy pants, a sweatshirt, and slippers are more than acceptable. And if you’re the type of writer who’s able to be proficient in such home attire, more power to you. Keep doing you. But if you ever find yourself in a funk, grasping for words and ideas that prove to be absent, perhaps putting on an actual pair of pants is the first step needed to make those words appear. You might be surprised at how good it makes you feel and how well your mind begins to work.

https://medium.com/inspired-writer/shoes-and-shirt-and-pants-required-b4426f958d8c

['Greg Lusby']

2020-12-07 20:22:15.709000+00:00

['Self Improvement', 'Nonfiction', 'Life Lessons', 'Writing', 'Writing Tips']

Partnering with Cloud Providers

Ryan Abernathey and Joe Hamman cowrote this blog post following discussion with the Pangeo Steering Council. The basic ingredients for a Pangeo deployment are a fast parallel storage system, scalable high-performance compute nodes, access to the internet, and software which makes all these elements work together for an amazing interactive data-analysis experience. Pangeo deployment architecture. Via http://pangeo.io/architecture.html We have deployed Pangeo on a wide range of different systems, from small university clusters to Top 500 supercomputers. We have also found that commercial cloud environments (e.g. Amazon Web Services, Google Cloud Platform, Microsoft Azure) are a particularly good fit for Pangeo. The ability to quickly scale compute up and down on demand fits well with the workflow of interactive big-data analysis, and cloud object stores work very well with Xarray, Zarr, and Dask. Additionally, the cloud offers the ability to compose tailor-made computational environments that fit specific scientific workflows, allowing scientists to be more efficient with their resource consumption. We have already benefitted from numerous partnerships with cloud providers, mostly in the form of grants of cloud credits. These credits have been invaluable in prototyping, debugging, and fine tuning the various components of our cloud architecture. Some cloud providers are understandably enthusiastic about Pangeo, as they see it as a way to attract new customers to their platforms. Moving forward, we think it is useful to articulate some general principles to guide potential future partnerships with cloud providers. In the spirit of Pangeo, we are sharing these principles openly and seeking feedback from both the the Pangeo community and the cloud providers. We are keenly aware of some past friction between open-source projects and cloud providers. Examples include MongoDB, Redis, who chose to modify their licenses to prevent cloud providers from monetizing their work without contributing back to the project. Closer to home, some tension has evidently emerged between the open-source Project Jupyter and the very similar yet distinct proprietary product Google Colab. We want to encourage cloud providers to collaborate with the Pangeo team. We wish to democratize the use of Pangeo within the scientific community by making the adoption and deployment of the platform easy, while maintaining the principles that keep Pangeo open. To that end, we hope that cloud providers who wish to improve the Pangeo experience for their customers pursue this goal through the open source process. Principles for Pangeo Cloud Infrastructure Here we articulate a few general principles which guide the more specific recommendations below. These principles mainly apply to academic research infrastructure. In contrast to, say, infrastructure for a startup, academic research infrastructure must consider relatively long timescales, unique challenges involving maintainability / sustainability, and a unique funding landscape. We believe that cloud-based academic research infrastructure, including Pangeo, should be Community driven —The needs of different institutions are fundamentally very similar. By collaborating, we can be more effective. This means leveraging existing projects like Jupyter, Dask, Zarr, etc. which already have community buy-in, and starting new ones very reluctantly. —The needs of different institutions are fundamentally very similar. By collaborating, we can be more effective. This means leveraging existing projects like Jupyter, Dask, Zarr, etc. which already have community buy-in, and starting new ones very reluctantly. Open source — In the cloud, infrastructure is code. In Pangeo, all our cloud infrastructure is essentially contained in an open source GitHub repo. There is no behind-the-scenes magic. Such code should be licensed in a way that enables the entire research community to reuse and build upon it. — In the cloud, infrastructure is code. In Pangeo, all our cloud infrastructure is essentially contained in an open source GitHub repo. There is no behind-the-scenes magic. Such code should be licensed in a way that enables the entire research community to reuse and build upon it. Modular — “all in one” solutions are cumbersome difficult to maintain long term. Separation of concerns is a key principle of good software and systems engineering. The cloud infrastructure needs of climate scientists are mostly the same as those of neuroscientists; each group should not be building everything from scratch. For example, both groups may want to use JupyterLab, Dask for computing, and Zarr for cloud storage, but may require different high-level analysis libraries. — “all in one” solutions are cumbersome difficult to maintain long term. Separation of concerns is a key principle of good software and systems engineering. The cloud infrastructure needs of climate scientists are mostly the same as those of neuroscientists; each group should not be building everything from scratch. For example, both groups may want to use JupyterLab, Dask for computing, and Zarr for cloud storage, but may require different high-level analysis libraries. Vendor neutral — The US currently has three main commercial cloud providers (AWS, Google Cloud, and Azure), plus many other smaller providers and academic clouds (e.g. NSF Jetstream). These providers compete with each other by rolling out unique new services. Academic research infrastructure should strive to use only vendor-neutral services APIs. (Kubernetes has been a game changer in this respect, allowing the orchestration of complex cloud services in a completely vendor neutral way.) If this principle is followed, it means we redeploy our infrastructure anywhere, preventing any one vendor from capturing the market, which could have negative consequences for the research enterprise. The last point was expressed elegantly in a blog post by Yuvi Panda. Pangeo Architecture is Still in Flux As anyone who uses Pangeo knows, we are quite far from a “stable release” (in the software-development sense). This doesn’t mean the platform is buggy and unreliable; it means that the core elements are still under active development. A great example is Dask Gateway, a multi-tenant server for securely deploying and managing Dask clusters. Dask Gateway natively supports Dask on Kubernetes and offers something the current iteration of Pangeo doesn’t, a secure and centrally managed Dask service. While the advent of Dask Gateway is quite exciting, it is also quite new and we’re still working out how best it will fit with Pangeo. This is just one example — there are numerous other nascent development efforts that we expect to disrupt the current architecture of Pangeo. How Can Cloud Providers Contribute? If we can realize the potential of Pangeo, many scientific fields will begin to seriously consider moving their day-to-day interactive workflows to the commercial cloud. This is an outcome that would be beneficial to both scientists and cloud-providers. So how can cloud providers help make it happen? Based on the discussion above, we have some concrete suggestions. Improve managed services — Pangeo works best when we can leverage the managed services (e.g. Kubernetes) offered by cloud providers. Cloud providers can look to Pangeo to highlight areas these services can be improved. Hopefully, this leads to full-featured implementations of these services on all cloud platforms and enhanced performance for things like deployment, autoscaling, heterogeneous clusters, and the use of spot/preemptible instances. Help develop deployment procedures — As we covered above, Pangeo is built on open infrastructure (e.g. Kubernetes). Cloud providers could contribute by documenting and streamlining the deployment procedure of Pangeo on their hosted infrastructure. We expect this would also lead to the cloud providers making some quality of life improvements to both their managed Kubernetes services and the Pangeo infrastructure. Contribute to the tools that make up Pangeo — The Pangeo Cloud Platform is really just a collection of open source software projects (e.g. Jupyter, Dask, Zarr, Xarray). These project are developed and maintained by a community of stakeholders that includes scientists, software developers, and infrastructure providers. Cloud providers hoping to see increased use of these tools on their platform should view contributing to these projects as a way to enhance their customers’ experience. To provide a tangible example of what this might look like, cloud providers could contribute to the Dask-cloudprovider project by expanding the list of supported cloud APIs. On the storage side, cloud providers could engage with the zarr spec development process to help the Pangeo community optimize our interaction with cloud object storage. Provide grants of credits — This is the obvious one, but it remains relevant. Many institutions are reluctant to invest in cloud until the value can be clearly demonstrated. But without credits to experiment, it’s hard to develop realistic demonstrations. So far, cloud providers have been very generous here, so that is an easy one and we hope to see this continue. Host Public Datasets — Storage is a major cost for Pangeo. Many of our datasets have high public value and would be well suited for public dataset programs. We are very happy that several cloud providers have already expressed interest in this possibility. Future Outlook As the different components of Pangeo — i.e. JupyterHub, Dask, Zarr — mature and become more stable on different cloud platforms, it will become easier and easier to deploy Pangeo. It may require just a single simple configuration file, or a few clicks on a dashboard. Reaching this point will benefit everyone, from the academic research community, to the growing number of startups in the climate data science space, to the cloud providers themselves. We hope we’ve provided a reasonably comprehensive overview of how the Pangeo Project can partner with cloud providers. We’re developing these thoughts in the open and encourage feedback from across the Pangeo community, including the cloud providers themselves. We believe that, by following the principles we outlined above, we can get buy-in from the more conservative sides of academia that are skeptical of commercial cloud as a research platform. We also feel it’s the best path for realizing the full potential of this still-young technology. We welcome comments below or on our Discourse forum.

https://medium.com/pangeo/partnering-with-cloud-providers-c795b1203f1f

['Ryan Abernathey']

2019-09-25 20:36:31.646000+00:00

['Cloud Computing', 'Science', 'Data Science', 'Pangeo']

How to Overcome the Fear of Failure

How to Overcome the Fear of Failure Start by changing how you see failure. It’s not your enemy — it’s your greatest ally. Photo by Elijah Hiett on Unsplash The fear of failure is what leads to failure. We all suffer from it. There are no exceptions. But for each one of us, failure means an entirely different thing. Being afraid to fail is not bad. But you’re afraid of the wrong kind of failure, and it’s holding you back. You fear not being good enough. You fear failing despite your best efforts. You fear losing way more than you love winning. You let that irrational fear take control over your life. You may end up having less tomorrow than you have today and this prevents you from trying. But you completely miss the fact that what you have today is far less than you deserve. It’s time to redirect that fear and use it to your advantage. Don’t try to get rid of your fear Understand that the fear of failure is more damaging than failure itself. If you want to succeed, you need to deal with that fear. But here’s the catch. I don’t mean you should overcome your fear. Instead, embrace your fear. Feel it. It’s an important part of you. Because this fear will keep you on your toes. It will keep you awake at night and force you to go over things again and again. It will push you to train harder and work better. Fear will be the reason you re-evaluate your plans time and time again. The fear of failure is your motivation to prepare for combat. It is what ultimately fuels your success. But you have to use it the right way. And you need to understand what real failure is. What you should be afraid of. Redefine your failure Getting rejected by your crush, losing your job, wasting money on a bad investment, not being able to do 20 push-ups. Stop seeing these things as a failure. Even if others keep calling them that. Those things aren’t failures. They are setbacks. Unless you give up on yourself, you’re not quite there yet. But you know what real failure is? Doing nothing! If you fear a bad outcome so much that you are terrified of taking a step, you will never reach any of your goals. And that is the failure you should be afraid of. Waking up in a week, a month, a year, or even a decade and not being any closer to your goals than you are today. That is failure. That’s what you should fear. That’s what pushes you to move forward. You need to start taking risks. You need to start taking action. I fear failure. Every single day. I fear that I wake up another day and have achieved nothing. That’s what I’m afraid of. Failure is doing nothing. Then learn to accept setbacks Things don’t always go as planned. Sometimes we hit a wall. Sometimes we lose the game. And that’s when growth happens. If you’re afraid to fail, you’re afraid to grow. So learn to deal with setbacks in a positive manner. Learn from your mistakes. But more importantly, try again with that knowledge. If you fall, get back up. You weren’t afraid of falling as a kid, were you? You wouldn’t be able to ride a bicycle if you were. Ask any daytrader on the stock market. They all burned at least one trading account in the beginning. $5000 or more, gone. But they are also the ones now making hundreds of thousands of dollars per day. Because they learned to accept it as a setback, not a failure. They all were afraid of making the same mistake again. But instead of giving up on the idea, they tried again. And their past failures helped them become better at it. And the same is true for every discipline. Whether that is sports, finance, relationships, or at work. You will inevitably fail at least once or twice. But it’s not failure as long as you get back up. Don’t be afraid of trying and not succeeding. Be afraid of not trying at all. Successful people work hard I’m sure you heard that a lot, and it’s true. But have you ever gave it any thought? What does it mean? Does it mean that successful people always work 80-hour weeks? That successful people always lift 10 pounds more than the rest? Yes and no. Working hard means working through failure. Everyone fails. Everyone loses. Sometimes you do everything right and still fail. Working hard at this moment means getting back up. It’s not about how many hours you put into your project, or how many reps you do on the bench. It’s that one moment in which your mind and body break down where it’s decided whether you are working hard or not. When you grab that towel, you have two choices. You can throw it, or you can take it, wipe the sweat off your forehead, and push yourself further. Successful people work hard because they don’t give up in the face of failure. They ask themselves why they failed and how they can prevent failing again. Then they try again. That’s what hard work means. Pushing through. Not giving in to self-doubt. Giving up is easy. That’s why not giving up is hard work. Understand your true potential One of the main reasons we fear failure is because we make ourselves small. We think we’re not that special. We’re not meant to be what we want to be. We don’t have what it takes. We think that if we try, we’re imposters, nothing more. We are not imposters! If you do it, and you keep doing it and you push through, you are everything but an imposter! I’ve seen friends of mine grow into beasts of men because they kept pushing themselves. They were pushovers before, now they could choke me with one hand. There’s no such thing as talent. Only hard work. And hard work means to push on in the one moment you’re on your knees. What you do up until that point doesn’t matter. The guy who’s lifting 50 pounds more than you isn’t working harder than you. The one who pushes through the pain, the one who comes back the next day to continue. That’s the one who works harder. Who you have to be or who you can become is not decided. Stop seeing yourself as an imposter. Stop seeing yourself as unfit. Work on yourself and discover your true potential. You have to take risks That’s the only thing that can lead to success. Taking risks. Leaving your comfort zone. Accepting setbacks. Pushing through. If you never risk anything, you will be in the exact same spot tomorrow as you are today. If you don’t take action, you fail. If you want to do something, do it. Yes, you can fall down. In fact, you will fall down. If you can pull it off on your first attempt, you’re really lucky. Two times I took an incredible risk in my life. The first time, I gave up my whole life to move halfway across the world to be with someone I only knew for a few months. If it failed, I would have wasted $4000 on travel costs, a broken heart, and my professional future. I sold everything I owned, quit my job, left my home. Imagine if it hadn’t worked out. My life would be in pieces. Instead, I live in a wonderful country, am married, and have a beautiful daughter. The second time, I quit my last job over a fight with management. Instead of looking for another job, I took the last $1000 savings I had to buy a computer. I wanted to become a freelancer and work from home. Be my own boss. But I had no experience whatsoever. Now I’m almost in my 6th year working from home. Both times I risked a lot, without knowing if I’d even make it. And because of this fear, I worked the hardest to not fail. Every setback I had back then, every problem that stood in my way, was one I could not accept. I was afraid. At times I was angry at myself. But I had to push through. I never worked as hard in my life as I did in these two situations. I put myself in a spot where giving up was not an option. Ever since then, I stopped believing in that “play it safe” mentality. Only if I take risks, I can really achieve something. So even if you think it sounds stupid, I’d encourage you to do the same. If you’re a quitter like me, you can find true strength by putting yourself in such a position. Final thoughts Overcoming your fear of failure is the wrong approach. But by redefining what failure means to you, you can shift your goals. Instead of fearing potential losses, learn to fear zero gains. Push through the pain. If you are the type of guy who throws in the towel, create a situation in which you can’t, no matter how much you’d like to. You should always have fear of failure. Because fear is an instinct. It raises your awareness and helps you make the right decisions in split-seconds. It will fuel your progress more than any dreams or hopes ever could. But you need to learn to fear the right things. Don’t fear setbacks. Instead, fear settling for less. Fear not taking action. Fear staying ordinary. Doing nothing is failure. So fear doing nothing.

https://medium.com/curious/how-to-overcome-the-fear-of-failure-72d78eaa3a3b

['Kevin Buddaeus']

2020-11-14 20:03:16.183000+00:00

['Life', 'Mental Health', 'Fear Of Failure', 'Motivation', 'Self Improvement']

Python Jupyter Notebooks in Excel

Python Jupyter Notebooks in Excel Embed Jupyter into Microsoft Excel and write Python instead of VBA Jupyter Notebooks in Microsoft Excel. Image by the author. It used to be an “either/or” choice between Excel and Python Jupyter Notebooks. With the introduction of the PyXLL-Jupyter package now you can use both together, side by side. In this article I’ll show you how to set up Jupyter Notebooks running inside Excel. Share data between the two and even call Python functions written in your Jupyter notebook from your Excel workbook! Jupyter Notebooks in Microsoft Excel. Video by the author. Getting Started First off, to run Python code in Excel you need the PyXLL add-in. The PyXLL add-in is what lets us integrate Python into Excel and use Python instead of VBA. To install the PyXLL Excel add-in “pip install pyxll” and then use the PyXLL command line tool to install the Excel add-in: >> pip install pyxll >> pyxll install If you’re new to PyXLL then take a look at the online documentation for first time users to help get you started. Please note, PyXLL is commercial software. It includes a free 30 day trial but requires a license to be used after the evaluation period. Once you have the PyXLL Excel add-in installed the next step is to install the pyxll-jupyter package. This package provides the glue between PyXLL and Jupyter so that we can use our Jupyter notebooks inside of Excel. The pyxll-jupyter package is installed using pip: >> pip install pyxll-jupyter Once both the PyXLL Excel add-in and the PyXLL-Jupyter package are installed start Excel and you will see a new “Jupyter” button in the PyXLL tab. Jupyter Notebooks in Microsoft Excel. Image by the author. Clicking this button opens the Jupyter notebook in a side panel in your Excel workbook. This panel is part of the Excel interface and can be un-docked or docked in a different location by dragging it. In the Jupyter panel you can select an existing notebook or create a new one. To create a new notebook select the “New” button followed by “Python 3”. Jupyter Notebooks in Microsoft Excel. Image by the author. Jupyter Notebooks in Microsoft Excel. Image by the author. How is this useful? Now you have a complete Jupyter notebook running inside of Excel! But what is this good for? How is this better than running a notebook outside of Excel? Well, now you can use Excel for working with your data and use Python to work on the same data. Use Excel as an interactive playground for organizing and visualizing your data, seamlessly switching to Python for more sophisticated tools. Use a Jupyter notebook as a scratch-pad for trying out Python code. Write Excel functions entirely in Python in a Jupyter notebook and test them out in real-time. Once you’ve developed a useful re-usable function add it to your PyXLL Python project. That way you can use the same function every time you use Excel. In the rest of this article I’ll show you how to: Share data between Excel and Python using your Jupyter notebook Write Excel worksheet functions (UDFs) in your notebook Script Excel with Python instead of VBA Getting data from Excel into Python Because PyXLL runs Python in the same process as Excel, accessing Excel data in Python and calling between Python and Excel is fast. To make things as easy as possible, the pyxll-jupyter package comes with some IPython “magic” functions for you to use in your Jupyter notebooks. %xl_get Excel data to Pandas DataFrames in Jupyter Notebook. Image by the author. Use the magic function “%xl_get” to get the current Excel selection in Python. Have a table of data in Excel? Select the top left corner (or the whole range) and type “%xl_get” in your Jupyter notebook and voila! the Excel table is now a pandas DataFrame. The %xl_get magic function as several options: -c or --cell . Pass the address of the cell(s) to get the value of, eg %xl_get --cell A1:D5 . or . Pass the address of the cell(s) to get the value of, eg . -t or --type . Specify a data type to use when getting the value, eg %xl_get --type numpy_array . or . Specify a data type to use when getting the value, eg . -x or --no-auto-resize . Only get the data for the selected or given range. Don’t expand to include the surrounding range of data. PyXLL has other ways of interacting with Excel to read data into Python. The “%xl_get” magic function is just a shortcut to make things easier! As the Jupyter notebook is running in Excel, all other methods (eg using the XLCell class, Excel’s COM API or even xlwings) are still available. TIP: You can assign a variable to the result of a magic function! For example, try “df = %xl_get”. Moving data in Python back to Excel Transfering data the other way around, from Python to Excel, works just as well. Whether you’ve used Python to load a dataset and want to transfer it to your Excel workbook, or if you’ve manipulated a data set from Excel and want the results back in Excel, copying data to Excel from Python is easy. %xl_set Pandas Dataframe to Excel range. Image by the author. The magic function “%xl_set” takes a Python object and writes it to Excel. Have a dataframe “df” that you want in Excel? No problem, just use “%xl_set df” and it will be written to the current selection in Excel. Like %xl_get, %xl_set has a range of options to control its behaviour. You can even use PyXLL’s cell formatting feature to automatically apply formatting at the same time as writing results to Excel. -c or --cell . Address of cell(s) to write the value to, eg %xl_set VALUE --cell A1 . or . Address of cell(s) to write the value to, eg . -t or --type . Datatype specifier to use when writing the value to Excel, eg %xl_set VALUE --type dataframe<index=False> . or . Datatype specifier to use when writing the value to Excel, eg . -f or --formatter . PyXLL cell formatter object, eg %xl_set VALUE --formatter DataFrameFormatter() . See cell formatting. or . PyXLL cell formatter object, eg . See cell formatting. -x or --no-auto-resize . Don’t auto-resize the range to fit the data. Only write values to the current selection or specified range. As with %xl_get, %xl_set is meerly a shortcut and all the other ways of writing back to Excel that you might have used with PyXLL will still work in a Jupyter notebook. Use Python plots (matplotlib/plotly etc) in Excel One of the great things about working with data is the powerful plotting packages available. Being able to plot a pandas DataFrame with a simple “df.plot()” is awesome! PyXLL has integration with all of the main plotting libraries so you can make the most of these in Excel too. This includes matplotlib (used by pandas), plotly, bokeh and altair. %xl_plot Plotting charts in a Jupyter Notebook and Excel. Image by the author. Use “%xl_plot” to draw any Python chart in Excel. Pass it any figure object from one of the supported plotting libraries, or use the last pyplot figure. Using pandas plot works great, eg. %xl_plot df.plot(kind='scatter') . The %xl_plot magic function has some options to control how it works: -n or --name . Name of the picture object in Excel. If using a name of a picture that already exists that picture will be replaced. or . Name of the picture object in Excel. If using a name of a picture that already exists that picture will be replaced. -c or --cell . Cell address to use as the location for the new picture. If the picture already exists this has no effect. or . Cell address to use as the location for the new picture. If the picture already exists this has no effect. -w or --width . Width of the picture in Excel in points. This has no effect if updating an existing picture. or . Width of the picture in Excel in points. This has no effect if updating an existing picture. -h or --height . Height of the picture in Excel in points. This has no effect if updating an existing picture. %xl_plot is a shortcut for the pyxll.plot function. Call Python functions from Excel Rather than constantly moving data between Excel and Jupyter and then running some Python code, you can call Python function directly from the Excel workbook! One of the main use-cases for PyXLL is writing custom Excel worksheet functions (or “UDFs”) in Python. This is used for building models in Excel built from Python functions, which can of course themselves use other Python toolkits like pandas and scipy. How to Call Python Functions in Excel. Video by the author. You can write Excel worksheet functions in your Jupyter notebook too. This is a really great way of trying out ideas without leaving Excel to go to a Python IDE. Try it out for yourself. Write a simple function and then add the “pyxll.xl_func” decorator to your function: After you’ve entered the code and run the cell in Jupyter that Python function will immediately be available to call from the Excel workbook. It’s not just for simple functions. You can pass whole ranges of data to your function as pandas DataFrames and return any Python type, including numpy arrays and DataFrames! You can tell PyXLL what types to expect by giving the @xl_func decorator a signature string. For example, try out the following: Now you can write complex Python functions to do data transformation and analysis, but orchestrate how those functions are called or sequenced in Excel. Changing the inputs results in the functions be called and the calculated outputs update in real-time, just as you would expect! Script Excel with Python instead of VBA Did you know that everything you can do in VBA can also be done in Python? The Excel Object Model is what you use when writing VBA, but the same API is available in Python as well. See Python as a VBA Replacement from the PyXLL documentation for details of how this is possible. In a Jupyter notebook running in Excel the entire Excel Object Model is available and so you can script Excel in exactly the same way you might do in the Excel VBA Editor. Because PyXLL runs Python inside the Excel process there is no performance penalty for calling into Excel from Python. It is also possible to call into Excel from an external Python process, but this is generally much slower. Having a Jupyter notebook running in Excel makes everything more convenient too! Use PyXLL’s xl_app function to get the “Excel.Application” object, which is equivalent to the Application object in VBA. Try something like getting the current selection and changing the cell interior color. A great way of figuring out how to do something with the Excel Object Model is to record a VBA Macro and then translate that macro into Python! The PyXLL docs page Python as a VBA Replacement has some tips on how to do that. Scripting Excel using Python in a Jupyter Notebook. Image by the author. Summary Python makes a poweful alternative to VBA. With PyXLL you can write fully featured Excel add-ins entirely in Python. Excel is an amazing tool for interactive computation. Adding Python and Jupyter takes Excel to a whole new level. Code written in Jupyter notebooks can easily be refactored into standalone Python packages to create Excel tool-kits to power intutitive workbooks and dashboards. Any Excel user will be able to take advantage of Python tools written using PyXLL without needing any knowledge of Python. If you want to find out more then download and try PyXLL for yourself or contact me. I’ll be happy to answer any questions you might have and find out how PyXLL can help you! Links

https://towardsdatascience.com/python-jupyter-notebooks-in-excel-5ab34fc6439

['Tony Roberts']

2020-12-23 15:30:07.957000+00:00

['Python', 'Jupyter Notebook', 'Excel', 'Microsoft Office', 'Programming']

Why Subnautica is one of the best games I’ve played this year

Why Subnautica is one of the best games I’ve played this year A unique setting, an engaging story, and intentional design make this game stand out I can count on a few fingers the number of times that playing a video game has left me truly terrified. There are a few scenes in The Last of Us and its sequel that would be on the list, as well as a few other games that boast equally scary moments. But the thing about video games is that they’re often designed so you can beat them, which means that (usually) even the biggest bad guys can be beaten down with enough time and energy. However, there are some games where the most threatening enemies can’t be beaten. All you can do is hope to avoid them. Subnautica is one of those games (though it’s also much more, which I’ll explain below). Subnautica is definitely not a scary game, but it has moments of pure terror and adrenaline that have already terrified me multiple times. The atmosphere in the game is incredible, and its design has kept me coming back many times. I love when video games break off from genre tropes and create something truly unique. Through its detailed setting and close commitment to engaging gameplay, Subnautica cements itself as one of those rare games. What Subnautica is and how you play it First, a quick description. Subnautica is an open-world (ish) survival game set on a planet where water is everywhere. The game opens as your character’s ship goes up in flames, prompting a crash landing in the middle of this mysterious ocean. The ship is beyond repair, so within a few minutes of playing you realize that long-term survival on the planet is your only hope of living. And well over 90% of that survival will take place underwater. There isn’t much exposition — the entire opening of the game doesn’t take long at all — so you’re dropped into the world pretty quickly. There’s a list of things to find and craft, and the more you find the more opens up pretty quickly. It’s also worth noting that Subnautica is not procedurally-generated. There are dangerous, terrifying areas to find, but they’re intentionally mapped pretty far away from where you start out. The mechanics of the game involve swimming to ever-greater depths to find materials and resources. With these in hand, you can build an underwater base, pipe in breathable air from the surface, and even build underwater vehicles. The world is tough and inhospitable, but before long you can make it much more inviting. Why I love Subnautica Swimming through the waves and exploring the world have been one of the most enjoyable video game experiences I’ve had in forever. Most of the planet is bright and colorful, and the varied topography of the ocean floor keeps the gameplay from getting too repetitive. There’s a sense of wonder that’s so enthralling, and even though I’ve played for several hours I don’t feel like I’ve come anywhere close to finding even half of what’s out there. I bought Subnautica because it was on sale and because I wanted something to scratch the itch that Outer Wilds left me with a few months ago. The games are different in many ways: Outer Wilds is based purely on story, is much shorter, and is a game about exploring in space. But the themes of exploration, searching for answers, and navigating incredible worlds are present in each title. There’s a story in Subnautica, and what I’ve found of it so far has been pretty interesting. However, it’s clearly complementary to the survival experience rather than the sole objective like it is in Outer Wilds. I have to wait for new message to come to my radio before I can progress much further, giving me plenty of time to work on my base and find materials for vehicles. When that next message comes, though, I’ll be ready. Why Subnautica is like nothing else out there But what I keep coming back to in Subnautica is the sense of wonder that I get by swimming through its world. The plant and sea life is so varied, so incredible, that it’s easy to see how much work went into its design. And since progression has been so well designed, I’m rarely wondering what I should build next or where I should be exploring. You can do everything at your own pace, but the game is pretty generous with hints and tips. And the moments of pure terror are exhilarating in ways no other game can match (at least for me). I don’t play horror games often, so I’m used to levels where even the biggest bad guys will eventually be conquered. And in truth, that’s a pretty unrealistic setting for a science fiction survival game. Here, there are underwater creatures called “leviathan class predators” that I just can’t do anything against. I can avoid them by staying in more shallow waters, but I need to go deeper to find everything and progress the story. When I see one in the distance, it reminds me how small and weak my character is. No other game has done that for me.

https://medium.com/the-coastline-is-quiet/why-subnautica-is-one-of-the-best-games-ive-played-this-year-65fd6359c263

['Thomas Jenkins']

2020-09-21 17:03:57.617000+00:00

['Gaming', 'Design', 'Culture', 'Writing', 'Videogames']

Python HOW: Image processing for OCR using OpenCV

If your image has random noise, uneven illumination, holes in front objects, etc. There are few things that you can do before posting your image to a computer vision API. In this article, we go through few processing techniques to boost OCR results using OpenCV TL;DR: full code Install OpenCV Install OpenCV using your preferred package manager You might want to create a virtual environment first Read the image I will use the cover of the 1st edition of one of my favorite books as an example. Let’s first read the image, specifying the colour type of the image to coloured. This will read the image in the default colour format in OpenCV which is BGR (Blue-Green-Red). We will then convert the colour space to the more common RGB order (and for visualisation), and finally, write a small function to show the image without any interpolation: Docs for imread , cvtColor, imshow. To convert to gray, use code=cv2.COLOR_BGR2GRAY in line 14 Original: Image shape: 1360H x 1036W x 3C Crop image Mostly, you either have a box coordinates around the text (from a labelling tool), or you are only interested in part of your image. Our image is a 3D numpy array. To crop it, we can simply slice along the height and width: Cropped: Image shape: 580H x 900W x 3C Add border (i.e. padding) (doc) This might be useful for APIs with OCR models trained on documents (documents usually have white border)

https://medium.com/analytics-vidhya/python-how-image-processing-for-ocr-using-opencv-966acfae07a6

['Gabriel Harris Ph.D.']

2020-09-17 12:44:42.852000+00:00

['Optical Character Recogn', 'Python', 'Opencv', 'Image Processing', 'Programming']

Artificial intelligence holds great potential for both students and teachers — but only if used wisely

Published with Simon Knight in The Conversation: July 24, 2017 6.09am AEST Artificial intelligence (AI) enables Siri to recognise your question, Google to correct your spelling, and tools such as Kinect to track you as you move around the room. Data big and small have come to education, from creating online platforms to increasing standardised assessments. But how can AI help us use and improve it? AI has a long history with education Researchers in AI in education have been investigating how the two intersect for several decades. While it’s tempting to think that the primary dream for AI in education is to reduce marking load — a prospect made real through automated essay scoring — the breadth of applications goes beyond this. For example, researchers in AI in education have: developed intelligent tutoring systems that use student test responses to personalise how they navigate through material and assessments, targeting the skills they need to develop; investigated automatic detection of affect — including whether students are bored or confused — and used that to adapt materials they use; and built conversational agents or chatbots that can engage in discussions with students, even to support student-to-student collaboration. Artificial intelligence or intelligence amplification? These are new approaches to learning that rely heavily on students engaging with new kinds of technology. But researchers in AI, and related fields such as learning analytics, are also thinking about how AI can provide more effective feedback to students and teachers. One perspective is that researchers should worry less about making AI ever more intelligent, instead exploring the potential that relatively “stupid” (automated) tutors might have to amplify human intelligence. So, rather than focusing solely on building more intelligent AI to take humans out of the loop, we should focus just as much on intelligence amplification — or, going back to its intellectual roots, intelligence augmentation. This is the use of technology — including AI — to provide people with information that helps them make better decisions and learn more effectively. This approach combines computing sciences with human sciences. It takes seriously the need for technology to be integrated into everyday life. Keeping people in the loop is particularly important when the stakes are high, and AI is far from perfect. So, for instance, rather than focusing on automating the grading of student essays, some researchers are focusing on how they can provide intelligent feedback to students that helps them better assess their own writing. And while some are considering if they can replace nurses with robots, we are seeking to design better feedback to help them become high-performance nursing teams. UCL Professor Rose Luckin on artificial intelligence and the future of learning. Impacts on what we teach But for the use of AI to be sustainable, education also needs a second kind of change: what we teach. To be active citizens, students need a sound understanding of AI, and a critical approach to assessing the implications of the “datafication” of our lives — from the use of Facebook data to influence voting, to Google DeepMind’s access to medical data. Students also need the skills to manage this complexity, to work collaboratively and to innovate in a changing environment. These are qualities that could perhaps be amplified through effective use of AI. The potential is not only for education to be more efficient, but to think about how we teach: to keep revolution in sight, alongside evolution. Another response to AI’s perceived threat is to harness the technologies that will automate some forms of work, to cultivate those higher-order qualities that make humans distinctive from machines. Simon Buckingham Shum on learning analytics versus cognitive automation. (talk starts at 20mins) Algorithmic accountability Amid growing concerns about the pervasive role of algorithms in society, we must understand what “algorithmic accountability” means in education. Consider, for example, the potential for “predictive analytics” in flexi-pricing degrees based on a course-completion risk-rating built on online study habit data. Or the possibility of embedding existing human biases into university offers, or educational chatbots that seek to discern your needs. If AI delivers benefits only to students who have access to specific technologies, then inevitably this has the potential to marginalise some groups. Significant work is under way to clarify how ethics and privacy principlescan underpin the use of AI and data analytics in education. Intelligence amplification helps counteract these concerns by keeping people in the loop. A further concern is AI’s potential to result in a de-skilling or redundancy of teachers. This could possibly fuel a two-tier system where differing levels of educational support are provided. What does the future hold? The future of learning with AI, and other technologies, should be targeted not only at learning subject content, but also at cultivating curiosity, creativity and resilience. The ethical development of such innovations will require both teachers and students to have a robust understanding of how to work with data and AI to support their participation in society and across the professions.

https://medium.com/age-of-awareness/artificial-intelligence-holds-great-potential-for-both-students-and-teachers-but-only-if-used-3c0a212f81db

['Simon Buckingham Shum']

2020-04-23 09:39:24.875000+00:00

['Big Data', 'Artificial Intelligence', 'Learning Analytics', 'Data Science', 'Education']

Easily build a REST API with Spring Framework

# The Concept Before I even start explaining how to create an API, you should first know what this thing called “API” is. To begin with, API stands for Application Programming Interface, Wikipedia explains it as: A computing interface that defines interactions between multiple software intermediaries. It defines the kinds of calls or requests that can be made, how to make them, the data formats that should be used, the conventions to follow, etc. Let’s try mapping it to a specific example: Imagine you have a portfolio web page, where you share some information about yourself, like interests, side-jobs, professional experience, projects, and so on. Now you want people who follow you, to be always up to speed about your Spotify preferences. You may think about manually going to your Spotify account and copy your liked songs, it may work if you are an inactive user, however if not, it will quickly become a cumbersome task. That’s when the API word comes in, Spotify and a lot of other companies already developed their APIs, so people like you can avoid problems like this. developer.spotify.com In such a context, you will simply need to contact their API and request all the data that may fulfill your needs. In this case, your liked songs. An API can be described as an application that exposes services without the need of having a front end. Let’s now create our API example so we can easily understand what has been explained so far.

https://medium.com/analytics-vidhya/easily-build-your-rest-api-with-spring-framework-80941c359d44

['Rafael Martins']

2020-12-18 16:09:02.383000+00:00

['Technology', 'Software Engineering', 'Java', 'Spring Framework', 'Programming']

Is Medium’s New Logo A Sign Of Bigger Problems?

Is Medium’s New Logo A Sign Of Bigger Problems? A quick look at what’s happened with Medium over the last week Photo by Ben White on Unsplash Medium has implemented a lot of changes over the last week. New personal profile designs, writers on the front page now (finally) have their names listed and a new logo was launched. But what concerns me most is the new logo. When I first saw the logo, I thought my webpage had an error and didn’t fully load. Clearly, I’m not alone. This logo is so bad it makes me question everything about Medium. It appears logic and common sense have gone out the window. Why would I say something that extreme? Because if your branding isn’t clear, you failed. It appears Medium is just changing things to change them, and there is no clear vision. That’s really scary. Say you share a self-published post with someone from Medium. It’s their very first time encountering the website. What do they see? They see this. Medium has no branding on the page other than the weird … logo. It makes a self-published post look like a blog with a free Wordpress theme. Wordpress.org Doesn’t that look pretty familiar? Just hide the side bar and they are almost identical. These web pages are not unique. In fact, they are just BORING. It’s just plain vanilla ice cream in a rocky road world. More on this concept here. And that’s a problem. Is it possible I’m overreacting? Sure. I could be. But branding matters. End user experience matters. Here’s the homepage if you’re not logged into an account. Okay, that’s better. I guess that’s a spotlight made of words… maybe? Here’s what a post in a post in a publication looks like for a first time reader. I like the Write Stuff logo there, because that really helps the overall experience. But the funky … Medium logo really looks like an error. It looks like a mistake right there in the top corner. This new change makes publications even more important than ever before. And there was already a serious publication problem on Medium, which I go into more detail about in the post below. A Final Word What concerns me most about the new logo is the disconnect with the end users. Medium is nothing without the writers. Medium will cease to exist without people having fresh content to read on the website. Let me ask you a question. How do you feel being a writer on Medium? Do you feel like you are valued, or are you always playing catch up to the constant changes that don’t really seem to help you as a writer? I love Medium, but I’m very concerned about Medium’s future. As a writer, I’d love to see some real improvements, such as really customizing your homepage to see content that you want to see. Maybe having the ability to tip writers for a great post (because payment is not based on claps or engagement anymore). Using more than the bogus time-based metric for posts where anyone writing poetry or anything shorter is not immediately penalized. Even tiered subscription levels could be good (instead of $5 per month you could pay $10 or $20 per month) where you are able to pay writers better while also supporting the growth of Medium. As an end user and reader, I’d love for Medium to just have more clarity and stop making things more confusing. It will be interesting to see how this all pans out in the future.

https://medium.com/the-partnered-pen/is-mediums-new-logo-is-a-sign-of-bigger-problems-101f8dd84b44

['Jim Woods']

2020-10-21 17:03:24.098000+00:00

['Marketing', 'Content Marketing', 'Medium', 'Writer', 'Writing']

Three Ways to Start Building Your Email List

Writers need email lists. I can’t state that any more plainly. If you are a writer, you need a way to connect with your readers. You need to start thinking about that now. Today. I mean, it would be nice if you thought about it ten years ago. But if you didn’t, then today is next best. I wrote about why you need an email list and also the two things you need to get started. In case you missed those posts, here they are: Once you’re convinced you need an email list and you’re set up to start building one, the next question is how to find readers who want to give you permission to connect with them. Because what we’re talking about is permission marketing. It’s showing up in front of people who have asked you to be there. Not spamming unsuspecting folks who probably will never open one of your emails anyway. Email marketing has changed in the last few years. A lot. Remember when people used to eagerly open their emails? That doesn’t happen so much anymore. So even a well curated email list full of people who asked to be there and actually want the information will have what feels like a dismally low open rate. If half of the people on your list actually open your email, you’re absolutely killing it. Average is closer to 20 or 25 percent. But as you work on your email list, as you connect with your readers, you’ll notice something happen. You’ll have a subset of readers who always open. Who always click your links. Whose names you see come up again and again in comments on your posts. Those are your true fans. And when that starts to happen, it’s so exciting. But you have to get started with your list building if you want to connect with them. Today, I’m going to share a few relatively easy, obvious ways to start adding folks to your email list. Ask people who already like you. Obviously, right? Start with the low hanging fruit. Text your friends. Let them know that you’ve started writing about (your topic) and you thought they might be interested. Ask if they’d like to join your list. If they say yes, send them a link to a sign up form. (This post shows you how to do that.) Post on your social media feeds. Facebook, Twitter, Instagram — where ever you already connect with people. Add a simple call to action to your posts. Write a short bio to add to the bottom of all of your posts — here on Medium, on your own blog, or where ever you write. Add a line that asks folks to follow you to stay in touch. I mean, eventually you want something more effective than “let’s stay in touch,” and in a minute I’m going to show you how to do that. But for now, even that simple line will get your ball rolling. Shannon Ashley uses something very similar and has built her email list to 600 in just a couple of months. Don’t be afraid to ask people to do what you’d like them to do. In this case, join your email list so that you can stay in touch with them. Come up with one high-value, easy-to-digest thing to send in exchange for an email. When you’re ready for something a little more sophisticated (and effective) than “let’s stay in touch,” it’s time to create something to give your new followers. Your thing should be something that your readers can use right away. Something that’s a no-brainer — like getting ketchup with your fries. Something that won’t make readers feel like they’re committing to a huge amount of time or effort. When I first started doing this, I tried to use an eight-week novel-plotting course as my give away. It didn’t work. It was too big of an undertaking for people who don’t know me. So I pulled out the very first exercise. It’s my favorite anyway. Thousands — tens of thousands — of people have joined my email list in order to get that exercise. In my bio at the bottom of my email posts, I give away a secret weapon. That’s it. One simple exercise. One tool. I’ve used the two of them for three years and they are still effective. Occasionally, I’ll come up with something that ties directly into a specific post. For instance, maybe you’d be interested in signing up for a free seven-lesson anti-blogging for creatives class — since you’re clearly interested in connecting with readers. Or I might have a printable or some other sort of tool that I think some readers might find interesting. WARNING It’s so tempting, as a fiction writer, to offer a free short story or a chapter of your novel as your opt-in. Unless you already have a following, that’s unlikely to work very well. Ask yourself when the last time was that you gave up your email address in exchange for a short story from a writer you don’t already love. (Or even one you already love. Be honest!) You should be writing (blogging) about something other than your own fiction writing. No one wants to hear all about your process. I know that’s harsh, but it’s true. Your opt-in needs to tie into that. A short story is a good opt-in to put at the back of a novel. It’s not a great idea for the bottom of a blog post. You’d do better with “let’s stay in touch” because at least that promises more of the kind of post your reader just read — and doesn’t obligate them to read your short story. If you remember that your reader is the most important part of this whole equation, you’ll do fine.

https://medium.com/the-write-brain/three-ways-to-start-building-your-email-list-5dca9b584ecb

['Shaunta Grimes']

2019-04-19 18:42:31.908000+00:00

['Email', 'Work', 'Writing', 'Marketing', 'Success']

Growth Hacking Workflow: 5 Steps to Go from Cold to Warm Emails

In the past few months, as a Growth Hacker at NUMA Bengaluru and Co-founder of The Young Thinker, I’ve been experimenting with cold emailing. I’m telling you, emailing is still one of the most effective way to reach out and leverage a community. I developed a 5-step process to go from cold to warm emails: 1) Get targeted email lists Once you proficiently understand who your target audience is, you need to reach out to them in order to demonstrate how you can solve their problem. Emailing is still one of the best ways to do it, and here is how you can build that email list: Hunter on Linkedin By downloading the hunter chrome plugin, you will be able to get emails directly from Linkedin profiles. Let’s say you are targeting every CEO in Bangalore: start by searching for your preferences and grab every email you need using the hunter plugin. This plugin provides you with 150 email addresses for free per month. Serp Digger to scrap the web This tool is my favorite. You will be able to extract emails from Instagram, Pinterest, Facebook, and almost every website. No need to code — it’s simple and fast. Let’s take you through the process of scrapping Instagram to get entrepreneur’s emails in Bangalore: 1) Start your free trial on Serp Digger 2) Download Serp Digger plugin 3) Go on Google Custom Search Engine 4) Add a new search engine and copy paste http://instagram.com 5) Once created, click on a public URL to get the URL of your new search engine 6) Launch Serp Digger plugin on this new page and target your audience Then download your email list and copy-paste it onto a google spreadsheet. 2) Verify your email list Now that you have a huge email list of potential leads, you will probably be impatient to contact them. Wait though, we are not sure that all these emails are clean. You need to check if each of them are deliverable to, to avoid bounces. Indeed if your bounce rate is high, your email reputation will decrease and your chances to land in a spam box increase. Neverbounce to check and clean your email list Neverbounce is a great tool to verify and clean your email list. They will allow you to analyse your email list for free and give you an estimated bounce rate. You can then clean it by paying a fee depending on the number of emails you have. 3) Build emails, which convert Now you that you have a clean email list, it’s time to write the content of your email. Here are my 6 steps to build a mail that converts: Personalize your emails as much as you can. Start with who you are, show your target that you are not a bot. Display the credibility of your company. Explain the purpose of the email. Provide a Call to Action. It should be one link, be single minded. Offer to answer any doubts (show that you are available). 1)Hello <<First Name>>, 2)My name is Pierre, I am “role” at “Company name”. 3)“Company name” is an international company with 10+ years of experiences in… 4)We have built a product which allow users to….I invite you to check it through a free trial, I truly believe that you could benefit from it: 5)Start a free trial : “Link tracked” 6)If you have any questions, let me know, I will answer ASAP :). Kind regards, Pierre If you are not confident about the target, change the purpose and ask for recommendations: Instead of: I invite you to check it through a free trial, I truly believe that you could benefit from it. Use: I am contacting you, because I think you might know someone in your network who could find a real value in this product and might benefit from it. 4) Send your emails to the main box While it’s not hard to send emails today, it’s quite another thing to make sure people receive them in their main inbox. Yet Another Mail Merge to reach the main inbox Go back to your spreadsheet, where you copied and pasted your email list. Click on Add-ons and add YAMM for free. This tool connects your email list to your gmail account. You simply have to draft your email in gmail, as I showed you above, and YAMM will find it in order to send to your list. Furthermore, YAMM allows you to personalize your emails by naming each column in your spreadsheet. For example: Column A is “First Name”, if you put <<First Name>> on your draft, every email will be personalized with the first name (row by row). You can send 400 emails per day for free or 1500 emails per day, if you upgrade your plan and have a GSuite account. If you are facing troubles setting up your Gsuit account with YAMM, use CheckMX to see how to fix it. 5) Convert your leads Some of these cold leads will open your email and a part of them will even click on your unique link. It should drive them to a Landing page optimized to convert them (I wrote an article about Landing Page Optimizaiton here). Provide them with enough value, thus they would want to subscribe with the help of a powerful Call to Action. Make it clear, make it simple: LESS IS MORE. Convertkit to convert your leads Convertkit helps with creating a landing page or just the form that allows your visitors to subscribe. You’ll be able to personalize it as well as receive a data report. When you get a new subscriber, you can then enrol him in a sequence to send a drip email campaign — using automation processes. Finally, you can build a referral process to develop your acquisitions faster. Here is the workflow you should look for: 1st email: Free value (Instant value for what he subscribed) 2nd email: Free value (tips, pdf, ebook, articles…) 3rd email: Soft sales (Call to Action: Discover the product) 4th email: Free value (tips, pdf, ebook, articles…) 5th email: Hard sales (Call to Action: Buy the product) 6th email: Follow-up (Feedback if they bought, discount if they didn’t) Sending cold emails is not spamming. Sending cold emails to someone who doesn’t care about your offer is. The warm up process will start at the moment you show the right product, to the right people, with the right content. As soon as they will click and subscribe to your drip email campaign, 50% of the work is done. Then you’ll need to show them real value for free to build trust and position your company as the best solution to solve their problem.

https://medium.com/nookspot/growth-hacking-workflow-5-steps-to-go-from-cold-to-warm-emails-b1bdd7074234

['Pierre Guilbaud']

2018-10-02 09:32:29.469000+00:00

['Email Marketing', 'Startup', 'Digital Marketing', 'Entrepreneurship', 'Growth Hacking']

Depression Explained

Keep climbing: the view from the top is always worth the effort. Photo by Samantha Sophia on Unsplash What to do about depression As I write this, I’m aware that everyone’s circumstances and means are different. So while some people may be able to afford private therapy or even inpatient healthcare (and I’m one of these people), these are by no means an option for everyone. But happily (!) in my experience the most effective remedies for depression are affordable or even free. Here they are: 1) Hang tight All of the books, studies and doctors agree: depression does not last forever. When you’re in it, it feels like there’s no end in sight — no matter how many people try to reassure you otherwise. But once you’re out of it, the experience gradually recedes into a distant nightmare. It takes immense personal strength to find the will to keep pushing through it, day by day. But like climbing any strenuous mountain, the view from the top is worth the effort. You’ve just got to keep focusing on putting one step in front of the other. The world will keep on turning and everything will be waiting for you to rebuild on the other side, when you’re ready. I know all this because I’ve been there, many times. 2) Find some sort of purpose If you’re unable to carry out your normal work, find something you can do — and make yourself do it. You will feel better for it. I was lucky because I found staying at home unbearable anyway — some people can’t bear to get out of bed, but it’s worth it. The best thing I found to do was volunteering in a charity shop / thrift store, which are busy during the day so offer contact with people, but where the tasks are sufficiently menial, and the atmosphere positive (this last bit is important). You could also do a short course in something you’ve not done before that doesn’t require cognitive ability (eg pottery). 3) Force yourself to exercise Exercise produces endorphins, which make you feel good: it’s as simple as that. Unfortunately, exercise may be one of the last things you feel like doing if you’re depressed. So it’s just another one of those things you need to force yourself to do, even if it’s just a walk (preferably somewhere green). But the best thing you can do is get your heart rate going, as regularly as possible — you’ll notice the difference immediately. 4) Get therapy if possible But at the right time and with the right person. They say that therapy like CBT (cognitive behavioural therapy) is less effective when you’re in a full-blown depressive episode — but even then it’s still good to have the supportive ear of a therapist you connect with and respect. It’s particularly helpful when you’re recovering and looking to make changes to prevent depression happening again. If you can’t afford private therapy, see if there’s any online or free therapy you can do (eg through the NHS in the UK, or a charity). 5) Improve your sleep Bedtime was my favourite time when I was depressed — the chance for some respite and escape from the world for a few hours. But sleep disturbance is a key feature of depressive episodes, so do everything you can to help aid it. I listened to sleep hypnosis and meditations on youtube to get off to sleep and found them comforting and helpful. 6) Consider medication This is a difficult one. I’ve taken many different antidepressants over the past few years — enough to strongly recommend proceeding with caution. They can be very effective (after starting on one particular drug, I felt almost fully better within three days) but also dangerous (I believe that same drug tipped me into a manic episode a few months later). Other side-effects are common and grim, including the inability to go to the toilet, sexual dysfunction and much else besides. It’s a personal choice — one which is easy to make when you’re feeling desperate in depression, and one which can help give you a boost out of it. But it’s not a solution to be pursued in isolation of making the other changes listed here. And if you do take medication, make sure you’re monitored and supervised by a doctor, and taper off slowly when you want to stop. 7) Look after your gut It’s recently come to light that gut health and mental health are closely linked. So if you are feeling depressed, look into probiotics, glutamine or other health supplements that may make a big difference in helping you to feel better. 8) Cling on to whatever — and whoever — makes you feel good Wherever you find enjoyment when you’re depressed, pursue and savour it. Spend time with friends and family who love you without judgement. They will carry you through this. Sit in companionable silence watching escapist films. Don’t beat yourself up about eating chocolate or smoking cigarettes. In my view, it’s such a miserable time you deserve any precious small relief!

https://medium.com/invisible-illness/depression-explained-f2b177c740a4

['Claire Leveson']

2019-05-31 15:38:40.240000+00:00

['Depression', 'Life Lessons', 'Mental Health', 'Mental Illness', 'Psychology']

Importance Of Containers and Virtualization in Cloud Computing

We will now talk about virtualization and containers, which have become a very important topic in the software engineering field, primarily because there’s a lot of focus on it when it comes to cloud computing. But when these ideas came from? Initially, what used to happen is when you used to write code, you would have a DevOps steam or finance steam, which would ask you which box do you want to buy for this code? Capacity Planning So you would do something called capacity planning, which is basically a bunch of guesses. So you make a bunch of guesses and you tell that this is the amount of computing I need, this is the kind of memory I’ll be required for this application. I’ll be needing this much storage. Finally, you go to the shop and you buy a computer. Now, this is an investment, of course, you’re buying a computer. If you buy a small computer, the problem is what if your business scales up? So you went to the shop, you bought the computer, you made all that time and effort in investment and then what? Your business scaled up and you need to do this all over again. So what do you want to do is you don’t want to buy a small computer because that investment doesn’t make sense. You want to buy a large computer or a reasonably safe computer so that you don’t need to do this again and again. But the problem with this is that the initial hardware investment is very large. If you wanted a horizontal scale just on the basis of hardware, you would need to buy as many computers as possible. Better Approach So one of the approaches that organizations took was to let their employees use that single computer. But if you have multiple people using the same resource then, there’s going to be some contention. So you want to isolate resource usage as much as possible. The question was, can we do this for applications? Working Module Now, you have a program that requires a number of resources, which are usually memory, IO, processing, and disk. So that’s how you can think of your computer also. It’s a bunch of these four resources which can be used for running your program. Obviously, the more programs you have, the more resources you need, but you also want to do some sort of boundary management, which means that A does not interfere with B’s memory and C doesn’t interfere with A’s IO. And that responsibility is going to be taken up by the operating system. So now the operating system is the sole manager of these resources. When you write a program, you talk to the operating system saying that through your interface, I would like to book X amount of memory, Y amount of IO, and so on. So you’ve seen the diagram, that this program over there with the interface, is picking up some of the space in terms of resources. Similarly, you can have multiple programs that are going to be taking up slices of the resources that the operating system can provide and the remaining is going to be unused. The problem with this is that you can still have the same problems with shared compute, where, if the memory runs out because let’s say yellow takes up all the memory, then everyone else is upset. Virtual Machines What we would prefer to have is something like a very strong boundary, which is provided by something called virtual machines. And this concept is super interesting because the Virtual machine is like an operating system in itself. So it’s an operating system running on top of an operating system. Technically, you can have the Blue box in the diagram as a hypervisor, but let’s assume that it’s an operating system and you’re running this on top of it. So it’s like the matrix effect. The real world is being hidden from you and you can interact with this fake world that you have without concerning yourself with what other programs are running on the same hardware. You’re now mainly concerned with the virtual machine that you have been assigned, which has been given a set of resources. This concept makes a new business model possible, which is called cloud computing. Pros Of Virtual Machines The basic idea is huge companies like Amazon and Google have a lot of hardware laying about what they can do is take all of the spare hardware and rent it out to small businesses. For example, InterviewReady. I can go to Google or Amazon and say that “Hey, please run my site.” I’m going to pay you some rent money, but I’m not going to be making that big investment of maintenance and upfront cost of buying a computer like where I am going to place it. So that is the rent cost of placing the computer, of maintaining that computer is taken care of. I’m going to pay you some rent money, but I’m not going to be making that big investment of maintenance and upfront cost of buying a computer like where I am going to place it. So that is the rent cost of placing the computer, of maintaining that computer is taken care of. The other good thing is that my code doesn’t need to be platform dependent. I can think of a Windows computer and run Linux on top of it. So I have a 64 GB Windows computer, I can run let’s say, four or five Linux computers on top of it and my code doesn’t need to know that deep down there are windows running. The third thing is that this is very flexible, the provisioning of these resources is quite dynamic. All I need to do is shut down my Virtual machine and restart a new machine. I don’t need to go to the shop and buy a different computer. Amongst these three, I think platform independence is probably the game-changer here because if you remember Java when it came as a language so many people adopted because you no longer had to take OS considerations, you could push that onto the off steam. You just needed the .class file and you could run the program on any operating system. Cons Of Virtual Machines So this was a big deal because people could just go to these cloud providers and ask them for a virtual machine and they would get it very cheap. But one of the problems with the virtual machine is that when you’re running a program, you don’t want to start an entire virtual machine. It’s like booting up your computer. It takes some time. It takes a few seconds. And then the idea came up that, hey, you just need processing power, memory, disk, IO these four sources. Containers Taking all this into consideration, there came something like a lightweight Oses. They were a precursor for something called containers. Containers are effectively a form of virtualization. What they let you do is app isolation. You’re not going to be having all the features of OS isolation, you know virtual machines, but you don’t really need that. And the benefit is that you just need to tear down and build this lightweight container. So that’s faster when it comes to boom times. Interestingly, this process of building and tear down is called mounting and unmounting a desk. Pros Of Container In school, if you guys worked on CDs and stuff, we would mount and unmount disks that would be like a virtual machine, which would be allowing you to read the contents of the disk. Similarly, in a container, you actually specify the operating system and your disk requirements, and then the mounting process figures out the filesystem. Underlying file system, which you will be using through the interface of the container. So technologies like Docker have done the same thing that Java did for programming languages. It’s a way for us to move all OS considerations back to the developer. The developer can actually specify that these are the resources they need. This is the operating system I’ll be running on. And you don’t need to worry about the hardware so much. Docker will handle that. It’ll create an interface that will be interacting with the hardware or the virtual machine, whatever be the case. It will create a container on top of it and let your programming interact with the interface. When it needs more memory, it just asks and gets it. Cons Of Container So the advantage of using containers is clear, but the major disadvantage that I can see is that containers also considered a little slow. There are also possible firewall issues that come up because you have containers, although it’s much lesser in containers than a virtual machine in my personal experience. Overhead of container management is also not worth it really for simple applications like places where you know that you don’t need containers as such.

https://medium.com/datadriveninvestor/importance-of-containers-and-virtualization-in-cloud-computing-b0e312b78a77

['Vishnu Aravindhan']

2020-12-24 02:55:23.574000+00:00

['Virtualization', 'Software Engineering', 'Storage', 'Containers', 'Cloud Computing']

Reduce Your Footprint To Save Yourself, Not The Planet

Improve Your Future By Looking To The Past: I could spout on and on about why reducing your carbon footprint will benefit you. But I’ll keep my reasoning simple: Anytime you can apply an understanding of human evolution to your present-day life, you will be better off. We evolved to live in harmony with nature. We evolved to mostly eat lower on the food chain — think fruits and vegetables, not factory-bred meat and sugar-laden processed foods. We evolved to be on our feet, not on a comfortable couch or an ergonomic desk chair. We evolved to spend time outside. We evolved to derive pleasure from the simple things in life — socializing with friends and loved ones, not scrolling on a screen to find edited pictures to like or things to buy that you don’t need and are probably ecologically harmful. We evolved to live life in the slow lane, not the fast lane. We evolved to live surrounded by plants and rocks, not concrete and asphalt. Your ancestors lived very sustainable lifestyles. It was good for them, their neighbors, and the finite planet they lived on. The more you can emulate your ancestors in this respect, the better off you’ll be. Maybe that goes against the gospel of progress and futurism, but I’m a bit skeptical that many of the technological advancements we’ve made lately as a civilization — cars, TVs, smartphones, etc — have truly heightened our sense of well-being. Call me crazy, but sometimes I wish I could enter a time machine and go back 10,000 or 20,000 years. Sure, Stone Age people had hard, risky lives back in the day. They toiled to find clean food and water. They faced harsh conditions and were always vulnerable to violence and predation. Trouble awaited them with every step and every breath. Nonetheless, I don’t think they were significantly worse off than we are today. They didn’t pollute their air and poison their water with deadly chemicals. They didn’t stare at screens all day and play dangerous fake comparison games with each other. They didn’t ‘buy’ things they didn’t need. They didn’t eat processed crap. They didn’t lounge around and sit on their asses. They didn’t build concrete cages divorced from nature. They lived life to the fullest. And so can you. You can choose to adopt many of their wise practices, but you can benefit from the cars, antibiotics, supermarkets, and smartphones we take for granted. You can choose to embrace the aspects of modern life that are good for you and embrace the aspects of ancient life that are good for you. You have the best deck of cards any generation has ever had. If you play your hand correctly, you can live a better life than anyone ever has. And your lifestyle will become a smaller slice of the carbon footprint pie. Spend some time thinking deeply about what aspects of modern life truly benefit you. Then, think about what the ancients did that you too can do to cultivate your well-being. Take advantage of the pandemic to reconnect with nature and thereby reconnect with yourself. You may never have a better opportunity to bridge the gap between your authentic self and the inauthentic aspects of your self you present to the world.

https://medium.com/climate-conscious/reduce-your-footprint-to-save-yourself-not-the-planet-901944d2a928

['Danny Schleien']

2020-11-04 13:03:21.202000+00:00

['Evolution', 'Self', 'Environment', 'Carbon Footprint', 'Psychology']

Finished

Haiku is a form of poetry usually inspired by nature, which embraces simplicity. We invite all poetry lovers to have a go at composing Haiku. Be warned. You could become addicted. Follow

https://medium.com/house-of-haiku/finished-a85ec630947

['J.W. Parr']

2020-12-14 03:22:14.435000+00:00

['Poetry', 'Haiku', 'Books', 'Writing', 'Publishing']

Void: Self-Discovery Oracle Card

The void is the womb that births you into a truer version of yourself. It’s the hole in your heart where the infinite lives. The void is where you let go of the illusions that no longer serve you. Even though it feels like dying, the void is not where you die, it is where the lies you tell about yourself die. The void is the tunnel you pass through as you become both your future self and your original self all at once. Only that which serves you is allowed to through the tunnel. You must leave behind all that is toxic. Consider your time in the void sacred, for the void is where you meet the infinite. The void is where you meet yourself.

https://medium.com/just-jordin/void-self-discovery-oracle-card-d2bd31c2d247

['Jordin James']

2020-11-02 22:22:16.143000+00:00

['Self', 'Mental Health', 'Inspiration', 'Spirituality', 'Psychology']

I’m Suffering From LOPS—Maybe You Are, Too

I’m Suffering From LOPS—Maybe You Are, Too The emotions of the pandemic hit me late I remember where I was the night my friend texted me to tell me that “this coronavirus thing” was serious. They said I should have two weeks’ worth of nonperishable groceries on hand. I was in Brooklyn, and I scheduled a food delivery on Amazon Prime from my phone — mostly beans, rice, and pasta — as I walked to a bar to watch one of the Democratic primary debates. That was back in late February—approximately 4,000 years ago. The night I placed a laughably insufficient grocery order when I heard the pandemic might actually be serious. I still thought Warren might have a real shot at the nomination. How young we were! In the beginning, it felt novel. Yes, trips to get essentials were harrowing affairs, but for a while, nights hunkered down at home, drinking wine on social Zoom calls with friends, felt like a giant experiment. We were facing the unknown, but we were in it together. We sewed our own masks. We learned how to regrow scallions. We baked and baked and baked. Even the difficult parts of working remotely had a certain freshness; I carefully curated an aesthetically pleasing workspace in the nook by my kitchen window. For those of us privileged enough to experience the pandemic safely ensconced inside our apartments with plenty of groceries, this was fine. Now we’re within arm’s reach of setting our clocks back and weathering the season of early darkness, and it’s clear that most of us aren’t okay. I think I’m suffering from LOPS: late-onset pandemic sadness. I am not a clinical psychologist, and this is not a diagnosis — it’s just an acronym I made up. But I think many of us are feeling it. We burned through our reserves of “powering through” and “coming together” and “self-care” months ago. And sadness and loneliness and hopelessness have been leaking, drop by drop, into those empty tanks where our resolve used to be.

https://humanparts.medium.com/i-am-suffering-from-l-o-p-s-and-you-probably-are-too-8262834c6dc3

['Elizabeth Cauvel']

2020-10-20 16:03:20.294000+00:00

['Depression', 'Mental Health', 'This Is Us', 'Happiness', 'Coronavirus']

The Future of Artificial Intelligence

Last month I got the opportunity to pick the brain of some of the T500 nominees during The Next Web Conference 2018. In this article, I’ll share their views on a frequently recurring presentation topic at the event: Artificial Intelligence (AI). Not only did I ask them about the opportunities they saw, but also about the — at least as important — challenges and risks they identified. Daniëlle Tump (25) What are your opinions on Elon Musk’s view that AI could become more intelligent than the humans that created it? I’m in two minds. On the one hand, I do believe that AI can teach itself to become smarter than humans. But on the other hand, I think that if a human creates AI it can therefore control the limits in which it functions. For Brain Computer Interfaces (BCI) I don’t see any problems because it requires humans to read brainwaves. BCI still has a long way to go, before being able to function in a more complex manner. At present, BCI can be used in the healthcare system, for example. It can help people move, eat or steer their wheelchair. But it can also be used for entertainment purposes: changing the song you’re listening to just by thinking about it, instead of typing it on your phone or computer. Do you think there is sufficient knowledge about the brain to make optimum use out of BCI? Understanding the brain is a huge challenge on itself, let alone understanding each individual brain. Each brain is different, depending on the person and their surroundings. But I don’t believe we should delay further development of BCI, just because we don’t understand everything yet. There are already several useful applications, despite not having a complete understanding of the brain and its capacities. That said, it will become necessary to develop policies when BCI is used in daily life. If used for a polygraph, for example.

https://medium.com/the-outlier/the-future-of-artificial-intelligence-6c0200387ace

['Roy Klaasse Bos']

2020-05-05 10:34:25.979000+00:00

['Technology', 'Artificial Intelligence', 'Entrepreneurship', 'Study', 'Data Science']

Learn To Adapt: 5 Ways To Boost Your Adaptability

1. Get out of your comfort zone What forced us to grow adaptable in the first place was the lack of a comfort zone. Predators would hunt us in our favorite spots, food wouldn’t just wait for us in the refrigerator, and every wrong move was often deadly. But nowadays, we have monotonous lives, a stable income, a secure home, and no conflict. This is our comfort zone. We can live in it today and in 30 years. As long as nothing changes, we have all we essentially need. You aren’t looking for a better job right now, though you’re not entirely happy with the one you got. You aren’t looking for a new home, though you still hate that the living room gets quite cold in the winter and you have to let the heater run 24/7. And that’s what is keeping you in the same spot. Comfort. If you were to lose your job or home tomorrow, your first reaction would be shock. What to do now? You are unprepared. The comfort zone is a psychological state in which one feels familiar, safe, at ease, and secure. You never change your life until you step out of your comfort zone; change begins at the end of your comfort zone. ― Roy T. Bennett But if you stop accepting your current comfortable situation as given and constantly search for ways to challenge the status quo, you will grow more flexible and adaptable to change. Not only that, but you will learn to constantly improve your system. Start small. Go to a different restaurant next time. One that you’ve never been to before. They don’t offer any food items you like? Then order something new. The goal is to make changes — however small — to your routine. Routine is your enemy. If you get used to something, you need to try something else. Do not settle within the status quo. 2. Change the way you think One problem with the above is the way we usually think about tasks and outcomes. “That’s the way we’ve always done it” is a common phrase. But is it really the most effective way to do it? Quick thinkers are resourceful. And lazy. But not in a bad way. They are lazy as in, if there’s an easier or more efficient way to do something, they will find it. The trick is to first move outside your comfort zone, and then start working on making your new zone a new comfort zone. Then rinse and repeat. We cannot solve our problems with the same thinking we used when we created them. — Albert Einstein You need to change the way you think when deciding what to do and how to do it. Don’t take your current approach for the right way, the best way, or the true way. Look for flaws, find ways to improve it. Almost every system in the world can still be improved upon today. And those who dare to try it are often the pioneers of success and change. If you get used to change on a constant basis, then you will find it much easier to react to unforeseen changes. This will allow you to adapt quickly to new situations. 3. Accept failure and learn from it How you deal with failure is a direct catalyst for your ability to adapt. Do you give up? Then you’re dead. Do you try again without making any changes to your approach? Then you’re still dead. Do you analyze your mistakes and search for an alternative with better chances? That’s adapting. Learning from your mistakes and trying to improve on your past failure is adaption in progress. Adapting is for a big part trial and error. Where there’s no trial, there won’t be any errors, but also no progress. You don’t learn from successes; you don’t learn from awards; you don’t learn from celebrity; you only learn from wounds and scars and mistakes and failures. And that’s the truth. — Jane Fonda Growing a thick skin and being able to accept failure as a part of the process can help you with becoming more efficient. You need to stay resilient when things don’t go as planned. Because when you want to test your newfound adaptability in a real situation, that’s exactly what you’ll need to do. Many people have incredible problems with accepting failure. They try to ride a dead horse and refuse to move on. At the same time, they become hesitant to try new things, fearing it could only result in another failure. Accept failure and siphon it for valuable experience and knowledge. Don’t get caught up with the fact something went wrong, but look at why it did. Then use that to do it better next time. 4. Know your values As Sun Tzu once said: “If you know your enemy and you know yourself, you need not fear the results of a hundred battles.” In order to achieve change — the battle — you need to know yourself as much as you need to know your enemy. What is important to you? What are you willing to do in order to get where you want to be? If your will to remain the same is stronger than your will to change, then you will ultimately fail in your mission. Use your values as pivot points to set the machine in motion. It’s the leverage that will keep you motivated and engaged. It’s very important for people to know themselves and understand what their value system is, because if you don’t know what your value system is, then you don’t know what risks are worth taking and which ones are worth avoiding. — Ben Carson To really get to know your values, you need to analyze yourself thoroughly. Your values are more than your basic sense of justice or common sense. Your values are both intrinsic and conditioned priorities you set in life every single day. They define how ambitious you are, how resilient you are, and when you take risks, leaps of faith, and chances. Mark Manson — the author of “the subtle art of not giving a f*ck” — wrote a great article to help you find your personal values, here on Medium. Get to know your values. Because no matter how much change happens around you, your values remain the same. And they help you with taking the next step in a new situation. 5. Take a look at the bigger picture When we’re caught up with a task, we tend to become self-centered, our vision limited. We don’t think ahead. But being able to see the entire forest is important if you want to adapt to a new situation efficiently. You need to constantly remind yourself that there is always a bigger picture. Whether you are working as a creative for a client, or you are an author working on your next book. We always need to keep the entire picture in the frame. If you’re working in a company, you’re working as a part of a big system. If you can understand and improve not only your own tasks but the system as a whole, you will be able to make bigger changes. And if you understand how the entire system works, you can predict any changes that may affect you down the line. You can adapt before you will be forced to adapt. You definitely have to think of the perception of things before you actually do certain things. It may not seem like it’s a big deal to you yourself, but there’s a bigger picture. — Ezekiel Elliott Being able to adapt means being able to understand the whole system. If something changes, but we don’t know why or how, it will catch us off-guard. And then we might stumble and fall. Whenever a company or entrepreneur has written a success story, they did so by seeing the bigger picture. They did not only adapt to their immediate environment or situation, but to a whole ecosystem of change. Learn to understand the entire system. Question how and why things are interweaved, and you will have a much easier time adapting to certain changes.

https://medium.com/the-innovation/learn-to-adapt-5-ways-to-boost-your-adaptability-666142da5315

['Kevin Buddaeus']

2020-11-11 22:02:57.422000+00:00

['Entrepreneurship', 'Psychology', 'Self Improvement', 'Life Lessons', 'Change']

Digital Prototypes after a weekend? Yes, please!

The latest version of the Digital Prototyping Weekend took place at Holvi last Saturday and Sunday (13–14 October) A team working on their prototype. Photo credit: Pedro Cunha There were 8 amazing ideas, and if you missed what they were, here is a summary for you: Teamify acknowledges the utter importance of having a good team in order to succeed and taking ideas further. With Teamify you would be able to find people that possess the skills that your team is lacking. CryptoGallery is an app for art lovers that allows to buy art with cryptocurrency with swipe function to yay or nay your favorite art and that would be algorithm based and VR assisted. Car Doctor tackles on the problem of car mechanics, what if your car were to be treated as a patient and its “illnesses” were to be recorded on a unique profile? Transparent information and no surprises in bills. Talent Rocket focuses the attention on the shortage of tech professionals and offers an auction platform solution that helps mid and large companies to find and hire special tech talent. Sharbel Dahlan facilitating the event. Photo credit: Pedro Cunha OnGo Talk is an app that facilitates face to face conversations for travelers while they wait to continue their train or plane journey. Anything to alleviate the pain of waiting while traveling, right? Chill at Work focuses on getting the most of those seemingly dead times during a business trip by allowing users to connect with local events and activities of their interest. FloweRescue unites flower lovers and middle age flowers to avoid them going to the bin. How does it work? Florists offer their not-so-fresh flowers on an online platform, they find and lighten a new home. This environmentally friendly idea won the first place on the DPW due to its readiness and applicability. Good luck at Junction, you guys! Winner teams. Photo credit: Pedro Cunha Wolnut, a tool to help life and business coaches and their clients to achieve real transformation by closer tracking of progress and personal capability. So long procrastination and self-sabotage, hello goals! This idea is the winner of the second place with thumbs up for being a transferable concept. Thanks to all for the hard work! Great ideas that we certainly hope to see materialized in the near future. Besides Digital Prototyping Weekend, The Shortcut arranges a variety of other highly interesting events! Subscribe to our newsletter or follow us on Facebook to learn more.

https://medium.com/the-shortcut/digital-prototypes-after-a-weekend-yes-please-5bbf60441639

['Yesmith Sanchez']

2018-10-17 13:52:45.984000+00:00

['Hackathons', 'Startup', 'Event', 'Entrepreneurship', 'Prototyping']

What’s Really in the Way of Healing Your Traumas

What’s Really in the Way of Healing Your Traumas Unlearn these harmful mindsets that keep you stuck Photo: Camila Lorca/EyeEm/Getty Images Picture this: For years, you’re working on yourself, doing all sorts of therapy, healing ceremonies, meditations, and other obscure practices, only to find yourself triggered by an unforeseen event and back in a rut. You thought you figured out all your relationship issues and believed you were ready for The One, only to repeat the same patterns and end up frustrated and more self-critical than ever. Then, on top of everything, your mind gives you unsolicited advice: I should know better by now. When you believe that voice in your head, it’s easy to feel defeated and lose sight of the progress you’ve made in your healing journey. It’s frustrating, but you’re not alone. Over the last seven years as an embodiment coach, I’ve worked with hundreds of clients. There are three main reasons that people stay stuck in their traumas — and how to become unstuck. 1. Let go of false expectations. There is no end goal. Most people go through life working toward whatever they feel they need to have finally “made it” and “have it all together.” I’m sorry to tell you this, but you will never end up in a place where “it” is done. Every time you reach the end, you will uncover another layer of the onion. And peeling onions, as we know, will make us cry. The first step of healing trauma is really about false expectations. We’re setting ourselves up for failure if we expect to never be triggered or fuck up ever again. The antidote for this is simply acceptance; accept that you will always be sensitive, or needy, or a little bit controlling, or immature, or whatever it is. Welcome to the human experience! Practice acceptance and then watch what happens. 2. Stop playing the shame game. If there is one thing that keeps trauma in your life, it’s shame. Shame is the voice that says “there is something wrong with me” or “I’m not good enough.” Trauma is frozen energy stuck in your body. We can experience this energy as negative, paranoid, obsessive thinking. As fears and self-sabotaging narratives. As feelings of disempowerment, collapse, and de-motivation. Or as feelings of rigidity, perfectionism, and addiction. These feelings are a manifestation of the disconnect from our core, and an identification with the frozen energy of trauma we have inside, and that may feel excruciatingly painful to us. It may, indeed, make us misinterpret our rather “innocent” symptoms and believe there is something wrong with us. So what to do? The key lies in the concept of “I.” When there is something fundamentally wrong with “me,” then I’m doomed for life. Because the flaw is fundamental to myself, nothing I could ever do would take me beyond the feeling of not being good enough and not belonging. That’s really a scary place to live from. If, however, we change our perspective just a little bit, shift our focus slightly sideways, so to speak, and start perceiving our negative inner monologue as the symptoms of a wound that happened to an innocent child, a whole new dimension of feeling opens up. We can call it compassion. Compassion allows for space between the observer and the experience. It allows us to question the ideas that our inner monologue sets forth as true: What if it’s not true that I am broken and unworthy? What if I’m okay exactly the way I am, warts and all? It allows for regulating our fear response by breathing deeper. It allows for the courage to meet the frozen energy inside that so often feels like it is too big for us. Terrifying as it may be, when we don’t identify with that frozen energy, and instead find a resource in our acceptance and compassion for ourselves, we create space for that energy to unravel. Which brings me to the third point: 3. Create internal safety. Recently a client of mine asked me, “How do I know it’s safe to trust?” The truth is you don’t know until you do. Overcoming the fear response doesn’t happen by waiting for the fear to subside before you can trust. It happens by becoming intimately familiar with the fear in your system, so you can start creating a healthy distance to it and make space for curiosity instead. Start creating internal safety by honoring your feelings of unsafety. The idea is that if you have always felt X and reacted with Y and the result was Z, maybe you can react differently to feeling X and see if there will be a different result. This process of experiencing safety cannot be forced, however. That just puts pressure on yourself, and creates false expectations that lands you back in the cycle of shame. Instead, start creating internal safety by honoring your feelings of unsafety. It’s taken me years to acknowledge the fact that I am sensitive and that being in large groups of people overwhelms my nervous system. Only now am I starting to truly honor my need for my space when I’m in those environments, which involves saying “no” to certain interactions. My internal narrative went from: What’s wrong with me? Why am I feeling so insecure and small when I’m around those people? I need to force myself to be good enough by overgiving and overcaring. to: I honor my sensitivity. I know it’s okay to be vulnerable and not have it all together. What do I need right now? Do I need to be in nature, or ask for support? I feel safe because I am in touch with myself. This has been a slow process. There is no silver bullet for building trust. There is only the willingness to explore your assumptions, to experiment, and your ability to stay in connection with yourself. Staying in connection with yourself becomes more potent when you can express it and share it with others. That’s the true test: Can you honor your truth in the face of the other? When we do that, we are able to change the story of “I’m not good enough” into “I feel safe because I own all of me.” This reinforces that safety comes from within ourselves.

https://humanparts.medium.com/whats-really-in-the-way-of-healing-your-traumas-46f3012a297f

['Kasia Patzelt']

2020-04-02 16:42:45.899000+00:00

['Self Improvement', 'Mental Health', 'Life Lesson', 'Personal Growth', 'Psychology']

If You Want to Be a Succesful Writer, You Need to Try Copywriting

Like a whole bunch of people (and probably you, if you’re reading this!) I have always wanted to be a paid author, even since I was six and read my first work of fiction, The Magic Treehouse. But there was one small hiccup in my great plan: I thought I was bad at writing, and I didn’t know how to get better. I was way too intimidated to try to write fiction, but I’d never been interested in writing non-fiction. So I quietly shelved my goals of seeing my name on a book someday and dreamed smaller, less ambitious dreams. Then I ran across the concept of copywriting. What is copywriting? Have you ever read the product description of a bidet? Did you think, like me, that these spontaneously came into existence? Guess what: someone actually has to sit down and write those product descriptions. Same with a big, big chunk of the text you come across online. Copywriting means someone provides you with a brief — maybe a blog post, an ad, a product description — and you write it for them. You try to make it engaging, descriptive, filled with keywords so it will rank well on Google. You try to fit it in with the brand’s style. It’s an exercise in writing to a description. It’s challenging, it’s fun, and it’s rewarding. Photo by Kaitlyn Baker on Unsplash Not only financially rewarding but to me, copywriting was a way to gain validation that I was good at writing. It was my first paid writing gig before I’d ever blogged or heard about Medium. By spending maybe ten minutes a week writing a little 200 to 500-word blurb about a product, service, or experience, I funded most my pub trips. The math goes like this: I got paid around 1.5 pennies per word, I could write about 100 words per minute, and I usually researched the topic for about five minutes beforehand. If you do the math, this works out to around $7.50 every ten minutes, or $45/hour. I was a Masters student at the time, so the ability to work at a flexible rate for that kind of pay was tremendous for me. It wasn’t that much but it meant I could treat myself a bit more often than I would otherwise. And it taught me how to write to a deadline, how to write about anything (including, but not limited to, descriptions of toilets) and how to write well and quickly. Was I qualified? No. I was doing a Masters in bird conservation, so I had no history of writing copy, nor did I have any qualifications for writing. All I had was some free time and a liking for words. Photo by rawpixel on Unsplash The most important thing though, more than the money, was the idea that someone would pay me to write. At that point, to me, that was the ultimate form of validation for my writing. And it was awesome. Did that matter? Even without qualifications, the process was very straightforward. I applied on a website called copify.com by writing a short, 200-word copy example about a vacation spot. A week later, I was approved to write on their site. I gained access to a list of around 50 briefs submitted by clients. Each had a title, description, and word count. All I had to do was click on one, see if it was something I felt I could write about, and submit my draft. What kinds of things did I write about? Personally, I wrote an awful lot of product descriptions for furniture stores. It was easy to hit the minimum word count and the work was fairly repetitive, so I could write similar paragraphs for various products. However, occasionally I was more in the mood to write a longer, more interesting post. There were lots of options for that — some on health, some on travel, beauty and more. My screenshot from copify.com. There were so many options — it was rare I’d go on the site and not find anything to write about. And if I did, that just challenged me to broaden my horizons and write about something new.

https://zulie.medium.com/if-you-want-to-be-a-succesful-writer-you-need-to-try-copywriting-186cb497d047

['Zulie Rane']

2019-05-22 15:32:47.152000+00:00

['Entrepreneurship', 'Blogging', 'Freelancing', 'Copywriting', 'Writing']

5 Design Patterns every Software Engineer should know

When software engineers talk about Design Patterns, they usually talk about established and reusable constructs or architectures that address specific problems. For the most part, Design Patterns are defined independently of programming languages. If you are new to programming, you probably still don’t know, what I am talking about. Anyway, you probably used a Design Pattern at some point without knowing it. In the following, I introduce five Design Patterns that every Software Engineer should know about. Who creates and who uses Design Patterns? Well, everyone can. If we take a brief look into the history of Design Patterns, we will find out that it originates back to Christopher Alexander, an architect who wrote articles and books like “The Pattern of streets” or “A Pattern Language” in which he talks about actual architectural concepts, materials, and tools. At the core […] is the idea people should design their homes, streets, and communities. This idea […] comes from the observation most of the wonderful places of the world were not made by architects, but by the people. — Christopher Alexander et al., A Pattern Language, front bookflap This is, in my opinion, a very fitting metaphor because everyone can define a Design Pattern even though this is usually done by more experienced developers. You would expect an experienced software architect to build a highly sophisticated Design Patterns; however, each and every developer is in a unique situation and dealing with problems that require tailor-made solutions. Not every problem has to be solved by a Design Pattern, but an experienced Software Engineer recognizes a good opportunity. If you are relatively new to programming, you will probably not start to define Design Patterns after producing some “Hello Worlds”. It is more likely that you begin to gain experience through learning and “consuming” certain frameworks like Vue, Angular, or ASP. And while you do that you will probably learn about Design Patterns. When you climb up the technology proficiency ladder, you will learn even more until, at some point, you will no longer only consume technology frameworks and Design Patterns but also begin to create your own. But enough with the introduction. Let’s get to my list of the five must-know Design Patterns for software engineers.

https://medium.com/neotiv-gmbh/5-design-patterns-every-software-engineer-should-know-470c8b6c0b54

['Martin Leuckert']

2020-11-30 15:36:48.323000+00:00

['Software Engineering', 'Clean Code', 'Software Architecture', 'Programming', 'Design Patterns']

10 Ways to Avoid Bad Writing According To a New York Literary Agent

According to a New York literary agent, it only takes 5 pages to reject a book. Seems his taste is on point — his clients include Pulitzer Prize nominees, NYT best-selling authors and American Book Award winners. Having spent 2 years reading manuscript submissions at an indie publisher, I can relate. So many people have a great story to tell — and so many of them tell it very badly. Having a good story and telling it well aren’t the same. I saw an American Idol clip of JLo crying about sending someone home. It’s hard, she sobbed. You feel like you’re killing their dreams. That’s how I felt every time I read bad writing. How do you tell them? Because they think it’s good. You know what the problem is, right? Good writing is subjective… Problem is, there’s no such thing as good writing. Good is subjective. I might love a book — you think it’s a dud. Taste is personal. And on top of preference and taste, no two people read the same book. That’s why no one can teach good writing. College can’t. Writing classes can’t. Take as many classes as you want, they can’t teach you good writing because what makes writing good is entirely subjective. All they can do is teach you not to write badly. What trips up writers… The subjective nature of “good writing” trips up writers. When an agent or a publisher (or a publication) rejects their work, they think it’s subjective. Well, “that” person didn’t like it. So they submit elsewhere. Sometimes that is the case. Sometimes a piece of writing just isn’t a good fit, whether it’s for a publication or a publisher. Other times, it’s bad writing, but no one wants to say that. No one wants to be JLo telling a singer they’re not good enough yet. So they use the boilerplate rejection and say it’s not a good fit. You only need to read 5 pages to spot bad writing… I read a book called The First Five Pages, written by New York literary agent, Noah Lukeman, who says he only needs to read 5 pages of a manuscript to know whether to reject it or not. 5 pages. Think about it. You write an entire book. All that work — rejected in 5 pages. According to Lukeman, some of the most common reasons manuscripts get rejected are things I talk about over and over. Like: — A weak opening — Overuse of adjectives and adverbs — Lack of progression (pace) — Weak tropes and cliches — Rambling lack of focus When the book came out, the Editorial Director of Kirkus Reviews said it should be read by all novice writers. The book doesn’t tell writers what to do. It tells them what not to do. That’s the key to good writing; avoiding the most glaring mistakes. It’s not about “rules” for good writing. There aren’t any rules for good writing. I’m not fond of rules to begin with, least of all in writing. There’s little more dreadful than formulaic writing. Some of the best and most creative artists are the ones who break the rules mercilessly. They don’t just break them, they bend, twist and mutilate them until they are unrecognizable. That’s how art evolves. Writing included. The best writing advice doesn’t tell you what to do. It tells you what not to do. 10 Ways to Avoid Bad Writing The most common advice people give is “write more” — which is horrible advice because if you’re making mistakes, you’re going to keep making the same mistakes. And the habits become more deeply entrenched. Bad writing isn’t limited to using too many exclamation marks, run on sentences or grammatical errors. Often, bad writing boils down to lazy little habits that are easy to correct once you know them. So here you go. 10 ways to avoid bad writing. 1. Show, don’t tell. Writing is seeing. Don’t tell me he was disheveled. Tell me his shirt was half unbuttoned, his eyes were wild and there was blood above his right ear. Don’t tell me she was sobbing hysterically, tell me there was mascara running down her face as she wiped tears, snot and lipstick across her sleeve. And don’t tell me about the sleeve, it’s not important. Writers often describe too much. It minimizes the tears. If someone you loved was sobbing does what she’s wearing matter? Only if she’s crying about the clothing. Only describe what you need to. Good writing starts in the writer’s imagination, but should finish in the reader’s. Writing is seeing. You cannot paint with words if you don’t see in the first place. Good writing comes from good observation.

https://medium.com/the-partnered-pen/10-ways-to-avoid-bad-writing-according-to-a-new-york-literary-agent-b6e16f3c830f

['Linda Caroll']

2020-01-18 07:14:19.515000+00:00

['Books', 'Writing', 'Reading', 'Advice', 'Inspiration']

7 Best Websites for Freelancers in 2020

7 Best Websites for Freelancers in 2020 Some of the best freelancer marketplaces to get you started or get some extra gigs. Photo by Kristin Wilson on Unsplash As its name suggests, a freelancer has complete freedom to choose what and when to work. But, it has some serious drawbacks if done wrong. If you are someone who can efficiently manage work and life balance then freelancing can be a game-changer for you. Today, I’m here to talk about the best websites from where you can start your freelancing career. Before getting started, you need to understand the basic idea behind freelancing. It’s very important because it helps you find out whether you can be an online freelancer or not. Freelancing requires you to have a skill that you offer to clients and earn money in exchange. If you have a skill then you can be hired for specific tasks. Now, it depends on the task whether it requires physical presence or can be done remotely. For example, freelancing jobs for Handyman, Home Cleaning, Gardening, or Furniture Assembly requires physical presence. Whereas there are many digital skills (e.g. App Development, Graphic Designing, Content Writing, etc.) that can be offered from home. The websites I mentioned below are for those who want to work from home. Because it’s easier to provide digital services online and scale your business. So, without any further ado let’s have a look at my recommended freelancing job sites. Full disclaimer: I’m not a freelancer myself, though I have many friends freelancing. The sites here collected are recommendations from people with more experience than me on the field, I simply compiled them and presented them into the blog. I also have, at the moment of writing, no affiliations to any of the websites here listed. Additionally, the list is in no particular order, they are all great resources filling different needs and markets.

https://medium.com/the-innovation/7-best-websites-for-freelancers-in-2020-78112de6f7e9

['Juan Cruz Martinez']

2020-09-15 01:01:01.356000+00:00

['Startup', 'Productivity', 'Data Science', 'Programming', 'Freelancing']

UX Writing 101- Part 1

UX Writing 101- Part 1 What are UX writers, and how do they fit with the design process. The role of a content strategist/writer continues to evolve into its new form, which is a UX writer. As content is a vital part of the design process and the user journey, the role of a UX writer has never been more critical. And in this two-part article, I want to share with you what I discovered through my journey of learning and how UX writers create more tangible user experiences. Let’s begin, shall we? What is a UX writer? An interesting question. Isn’t a UX writer the same as a content strategist/writer. Well, for a long time, I held this view. Simply put, a UX writer is someone who writes for the user experience. Whereas a content strategist/writer typically creates content for the web. The role of a UX writer The role of the UX writer is to help connect the dots, guide and encourage the user to complete an action during the user journey. “Bringing writers in at the end of the creative process is like trying to put toothpaste into a tube.” — John Steinbeck And done effectively, UX writers help create a frictionless journey by writing clear and concise copy while maintaining your brand’s personality. As the text is designed and tested throughout the design process, placing your brand in a better position that can help drive more value. 3 top tips for UX writing #1 Be crystal clear Make your content easy to read and understandable. Remove any jargon words and offer context. Writers, in general, need to shift from using software language to language recognised by the everyday consumer. Tip: It’s always good to focus on the action that you want the user to complete. And use doing words, verbs, to craft the copy so that it relates to the action. #2 Be concise Get to the point. This doesn’t always mean shorter is better. But the words you put on a page have a job to do, so make them count. Tip: Put the most relevant content at the beginning of the sentence. Examine how your users consume your content. You’ll find that most, will read the first sentence, and then they’ll scan read. #3 Be useful A call to action is there to guide the user to the next step or complete a task. Use your copy to help your user reach the end goal. Tip: Make your call to actions resonate with what you want the user to do. And think about the journey. Is the user in discovery mode, and do they want to explore other useful content? Or are they in a transactional flow, in which case remove all obstacles and get out of their way? “Writing is easy. All you have to do is cross out the wrong words.” — Mark Twain Tone of voice So it’s all great that your UX writer is crafting copy that is clear, concise and useful. But how do you make your copy stand out? Do you remember in the film Sister Act, where Sister Mary Clarence is teaching the choir to sing? She points to Sister Mary Robert and coaches her to find her voice so she can be heard. Well, that’s what your tone of voice is for. Your tone of voice helps give your brand it’s personality, or it’s attitude as Sister Mary Clarence puts it. You want your brand to stand out against all the chit chat. And so your tone of voice needs to strike a balance of being clear and concise while being true to your brand’s personality. So there you go. A quick overview of what a UX writer is, what they do, and how they can elevate your design process. Helping you to craft better experiences for your user. Check out my follow up article, UX writing 101 — part 2, coming soon. Where we’ll explore how UX writers can help build on the design, who they work with, and how they help connect the dots.

https://medium.com/nyc-design/ux-writing-101-part-1-629d8b3a1d26

['Jas Deogan']

2020-04-21 13:34:35.606000+00:00

['Product Design', 'Design', 'New York', 'Ux Writing', 'UX']

I Left My Job At Google And Started My Own Business — Here’s The Truth About Entrepreneurship.

Lovers of The Sea has been in business for 8 months now. I’ve been working on it for a total of 11 months. I have learned so much in the process of building it and growing it and I want to shed some honest light on what it really means to be a solo entrepreneur in your late twenties building a completely bootstrapped business. Here are the five realities of the entrepreneurial journey: 1. Entrepreneurship is not Glamorous. No, it is not. It is a lonely grueling process of just keep going. We’ve been wired by the media to only see the result. You only hear about the entrepreneur who went from zero-to-seven-figures in her first year of business or the two-man startup team that just sold their business for $300,000,000. But when you dig deep into these stories, you realize the sheer number of years of failures, pivot points, and “figuring it out” 99.9% of startups must go through before “making it”. You uncover all the personal sacrifices, late nights, long weekends, self-doubts, criticism, financial insecurities, and troubles an entrepreneur endures throughout the process of building their business. We are bombarded with these glamorous headlines that we’ve become fine-tuned to only see — and think of — the result. But greatness is not in the result. Greatness is in the process. Reality #1: There will be so many tough days, so many zero-sale days, so many costs incurred without consistent revenue, so many glitches to fix, and much more uncertainty to maneuver. You will be crushed with self-doubt countless times, but you will carry on, and you will keep pushing because you’ll begin to understand that greatness is in the process, not the result. 2. Entrepreneurship will give you a true taste of what it means to sacrifice. Building on my previous point, get ready to say goodbye to your old life’s luxuries. You will not have the time (or money) to go out on dinner dates. Or to the movies. Or to festivals. Or to hang out with friends for drinks after work. Your mind will be consumed with so many problems, dilemmas, worries, and questions: How should we price this product? Why is our conversion rate so low? How do we grow our Instagram audience? How can we lower our shipping costs? How can we reach more people? What if we try this new approach to our email marketing campaign… This is all you’re going to think about, religiously for the first few months post-launch. There’s so much to learn and to figure out, that you will feel guilty socializing and spending money (which you don’t really have — especially if you don’t have a day job). For every dollar you spend on social activities, there’s one less dollar to spend on the business. For every hour you spend watching Netflix, that’s one less hour of reading on content marketing strategy. Reality #2: The sacrifice is necessary. It’s part of the equation. It was hard for me to accept this sudden change in lifestyle. At first, I thought it would only be temporary, and that soon things will flourish. But with time I’ve come to realize that this is the new reality of how things will be because it will take years of commitment to build a thriving sustainable business. And only when I came to accept this perspective that my thinking began to shift. I’ve now learned to see this sacrifice as an investment in myself, in my growth, in my journey to who I wish to become and where I want to take my life. Entrepreneurship will teach you that all great things are built by people with three qualities: an unparalleled self-belief, a willpower of commitment, and an ability to really cut-back and sacrifice for a greater ambition. 3. (Solo)Entrepreneurship is lonely. You are alone in this, and you are in it alone. This is especially true if you’re going at it solo. You will feel so lonely because your non-entrepreneur friends are still in their corporate jobs, still with that paycheque of security, traveling, partying, living life. And you can’t join them. They will invite you to chime in the fun and they won’t understand why you keep declining — which you will obviously do for three reasons: (1) you can’t afford it (2) you don’t have the time and (3) you have better things to do and focus on — you eat, sleep, work, repeat trying to build this thing you care so much about. You’re lonely because you’re marching through the struggles alone. In the grand scheme of things though, you’re sacrificing so much in your life now, with the dream of succeeding tomorrow. So, in the meantime, you’ll grow and learn to live in companionship with yourself. Reality #3: You will become your new best friend. Which isn’t so bad, considering how much more you’ll get to learn about yourself in the process. 4. Entrepreneurship isn’t about the “starting”, it’s about the “just keep going”. Starting is easy. We live in the easiest era in human history to start a business. It took me 15 minutes to get started: I registered my company, bought a domain online, and signed-up for an e-commerce online store. Boom. I just got started. All the tools to get started are online. Reality #4: Entrepreneurship isn’t about starting, it’s about the just keep going. Just keep pushing. Keep figuring out new ways of doing things and solving the never-ending problems that will arise. Greatness is in the process, not the result. This should be your mantra — a daily reminder that things will take time, so keep showing up today and stop obsessing about the future. 5. Entrepreneurship is an emotional rollercoaster riding straight into the unknown. There will be more tough times than good times. Get ready for this. That first sale will be so joyous. Five-star customer reviews will make you feel as happy as a kid licking an ice-cream on a hot summer day. Realty #5: For every great day there’s a series of incredibly difficult days you’ve got to deal with. And more than that, you’re literally swimming into the horizon. There is a massive opportunity ahead of you, but you don’t know if you will reach it. All you can do is believe in yourself and keep trying. So my advice to deal with these emotions of stress and anxiety would be to focus on learning. Ask yourself every day: am I still learning? You will immediately conclude that you are because you will look back to who you were when you first started this journey and you’ll realize this: I’ve come a long way.

https://medium.com/be-unique/i-left-my-job-at-google-and-started-my-own-business-heres-the-truth-about-entrepreneurship-55c3a4551902

['Omar Itani']

2020-07-28 20:20:11.501000+00:00

['Startup', 'Life Lessons', 'Entrepreneurship', 'Personal Growth', 'Inspiration']

Implementing different kernels of SVC Algorithm on the Iris Dataset

Code Here, we will go through the coding segment. The dataset used for this implementation is the iris dataset which can be imported from the sklearn library. Importing Dataset and Relevant Libraries/Modules Firstly, we will import the numpy and matplotlib for mathematical manipulation of data and plotting the graphs. Then we will import the svm classifier and the iris dataset from the sklearn library. import numpy as np import matplotlib.pyplot as plt from sklearn import svm, datasets iris = datasets.load_iris() The Iris Dataset (Image by Author) The Iris Dataset consists of 150 samples, each having 4 features listed: sepal length, sepal width, petal length, and petal width. Features in the Iris Dataset (Image by Author) The data has 3 classes: setosa, versicolor and virginica. Classes of Iris: Setosa, Versicolor and Virginica (Images from Wikipedia) Features & Target Numpy Array Next, we will take the first two features of the iris data, which are its sepal length and sepal width, both in cm. Our X variable will contain the features and y variable will contain the target. X = iris.data[:, :2] y = iris.target The Features & Target Numpy Arrays (Image by Auhtor) Model Creation Next, we will create models of the svm algorithms on the Iris dataset and use different kernels to observe the results. We will keep the value of C = 1.0 for all the models. C = 1.0 # SVM regularization parameter models = (svm.SVC(kernel='linear', C=C), svm.LinearSVC(C=C, max_iter=10000), svm.SVC(kernel='rbf', gamma=0.7, C=C), svm.SVC(kernel='poly', degree=3, gamma='auto', C=C)) models = (clf.fit(X, y) for clf in models) We have created 4 models: svm.SVC with linear kernel and value of C kept at 1.0 svm.LinearSVC (which uses the liblinear), with same value of C svm.SVC with rbf kernel svm.SVC with kernel = ‘poly’, degree = 3, gamma = ‘auto’ and default value of C Make Meshgrid Next, we will define a function to create a meshgrid to plot our 4 models. def make_meshgrid(x, y, h=.02): x_min, x_max = x.min() - 1, x.max() + 1 y_min, y_max = y.min() - 1, y.max() + 1 xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h)) return xx, yy Plotting Contours This function will be called to plot the decision boundaries for the classifiers. def plot_contours(ax, clf, xx, yy, **params): Z = clf.predict(np.c_[xx.ravel(), yy.ravel()]) Z = Z.reshape(xx.shape) out = ax.contourf(xx, yy, Z, **params) return out Plotting Next, we will define the titles of each plot and set up a 2x2 grid to plot our 4 classifiers plots. Then, we will fit the model one by one on the Iris Dataset and plot the results: # title for the plots titles = ('SVC with linear kernel', 'LinearSVC (linear kernel)', 'SVC with RBF kernel', 'SVC with polynomial (degree 3) kernel') # Set-up 2x2 grid for plotting. fig, sub = plt.subplots(2, 2) plt.subplots_adjust(wspace=0.4, hspace=0.4) X0, X1 = X[:, 0], X[:, 1] xx, yy = make_meshgrid(X0, X1) for clf, title, ax in zip(models, titles, sub.flatten()): plot_contours(ax, clf, xx, yy, cmap=plt.cm.coolwarm, alpha=0.8) ax.scatter(X0, X1, c=y, cmap=plt.cm.coolwarm, s=20, edgecolors='k') ax.set_xlim(xx.min(), xx.max()) ax.set_ylim(yy.min(), yy.max()) ax.set_xlabel('Sepal length') ax.set_ylabel('Sepal width') ax.set_xticks(()) ax.set_yticks(()) ax.set_title(title) plt.show() The following is the plot: Plot of SVC using various kernels (Image by Author) The sepal length has been taken on the x-axis whereas the sepal width has been taken on the y-axis.

https://medium.com/analytics-vidhya/implementing-different-kernels-of-svc-algorithm-on-the-iris-dataset-90908e55048a

['Mahnoor Javed']

2020-12-01 16:31:32.673000+00:00

['Machine Learning', 'Artificial Intelligence', 'Python', 'Sklearn', 'Data Science']

You Can Beat Procrastination in 10 Minutes

You Can Beat Procrastination in 10 Minutes Using time constraints to become more productive. Procrastination is one of the biggest, if not THE biggest challenge for daily productivity. Everyone struggles with it to some degree or another, and if taken to an extreme, procrastination can completely paralyze your life. While some people might have to turn to therapy to understand and overcome the deep seated reasons for their extreme procrastination, most people can beat it on a daily basis using a combination of discipline, willpower and a few simple exercises. Notice inspiration and motivation aren’t part of that procrastination-busting combo. That’s because inspiration and motivation are harder resources to come by than discipline and willpower. Inspiration and motivation are flakey and untrainable; discipline and willpower, however, are the exact opposite. Contrary to what most people believe, time constraints are incredibly effective strategies to beat procrastination, strengthen willpower and reinforce discipline. Time constraints are useful because the more time you allow yourself to finish a task, the more you’ll procrastinate and the longer you’ll take. This phenomenon is effectively described by the Parkinson’s law: “work expands so as to fill the time available for its completion.” This means, of course, that a simple task will become incredibly complex the more time you allow yourself to do it. A task that would normally take you three hours will suddenly expand to take over your entire week — if you give yourself a week to do it. The Parkinson’s law is, of course, more of a funny saying than a scientifically proven law. It’s a lot closer to Murphy’s law than to Newton’s laws of physics, but it’s main tenet resonates because, joke or not, deep down you know Parkinson is right. That’s why time constraints are so useful to beating procrastination and becoming more productive: when you restrict the time you have to do a given task, you have to get it done. No excuses. Just think of all the work you’ve always done last-minute, the famous inspiration provided by the pressure of an approaching deadline. Both self-imposed and external deadlines are helpful to boost productivity, but if you’d like to beat procrastination on your own, one day at a time, all you need are 10 minutes. The 10 minutes exercise is an effective creative writing technique that can be adapted to all kinds of work, as well as to solving problems in your personal life. The exercise is simple: set a timer for 10 minutes and just get started. All you have to do is make yourself work for those 10 minutes. If it’s a writing project, you have to write for 10 minutes. It doesn’t have to be good, you just have to get it done. If you’re trying to get your work day started, make your 10 minutes about answering emails, or returning phone calls, or drafting a few lines of the next project you have coming up. Again, it doesn’t have to be good work. You just have to make yourself do it for 10 minutes. No looking at your phone, no open a new tab on your browser to check the latest news or Twitter. Exclusively work. Once the 10 minutes are up, you’re free to do whatever you want. But here’s the beauty of this exercise: once time is up, you’re going to be on such a roll you won’t want to stop what you’re doing. You’ll just keep going. 10 minutes are all it takes to get warm up your engines for the day, and from then all, it’s all momentum. The 10 minutes exercise is great because it isn’t daunting. It’s not asking you to have a productive day from morning to evening, all it’s asking is that you sit your butt on a chair and get something done for 10 quick minutes. “I can do 10 minutes,” you’ll think. And before you’ll know it, it will have been an hour. Trust me. This exercise wasn’t my idea. I first learned about it in a creative writing class, and I’ve seen it replicated and talked about in all sorts of places. It’s tricky to tell who first came up with it. My guess? A frustrated writer who couldn’t figure out how to fill a blank page until she realized all she had to do is get started. That’s all you have to do as well, get started. The pomodoro technique is a very popular productivity strategy.

https://medium.com/a-life-of-words/you-can-beat-procrastination-in-10-minutes-88839d4716be

['Renata Gomes']

2020-11-03 19:33:02.098000+00:00

['Self Improvement', 'Life Lessons', 'Writing', 'Self', 'Productivity']

Why You Should Read Every Day

You get ideas in and you get ideas out — it’s called thinking. When you read, you are being immersed in ideas, whether they are fictional or non-fictional. You are in a world of rhetorical thinking. You are using the language being written down to consider what is going on in the written world you are reading. Reading is an exercise for the mind! Any mental stimulation is good for the brain and helps as you get older. Many studies have shown that reading improves memory, brain elasticity, and overall brain function. A study done at the Fisher Center for Alzheimer’s Research Foundation found that those who participated in mentally challenging activities (like reading) most often had a much slower rate of decline in memory compared to those who didn’t do mentally challenging activities. Reading is relaxing. Reading can be a stress reducer in one’s life. Grab a cup of tea (or coffee) and just take a moment to read before your day starts or right before your day ends. It will reduce some stress in your life. Reading enhances your vocab skills. Who doesn’t love to sound smart? Reading — especially diverse books — will help to enhance your vocabulary skills. It will also help your writing skills. Just make sure you are reading a diverse set of books and not the same thing over and over again! Reading is free entertainment. You can greatly reduce your fun/entertainment budget and save some money! Go to your local library and grab a book or two a week. Read in your free time and voilà you just save so much money by not going to the movies. Do you have presents to buy during the holiday season? Save money this way. Tightening your budget to contribute more to retirement savings? Save money this way!

https://medium.com/curious/why-you-should-read-every-day-c450a9535245

['Sm Sommer']

2020-08-18 17:29:57.234000+00:00

['Literacy', 'Reading Community', 'Mental Health', 'Books', 'Reading']

Gestures and MVVM

Programming Gestures and MVVM How to properly propagate gesture updates in an MVVM architecture I have never worked with gestures in iOS. Seems weird, but it’s the truth. This week, I had to integrate a gesture in an app to test a couple of things that we are developing, but I struggled a bit to make it work properly with our MVVM architecture. At Bending Spoons we are extremely eager to help out our colleagues and to share what we know. Lucky for me, I have a colleague who worked on that same issue before and shared a nice trick to solve the problem elegantly. I thought that if I benefitted from this hint, someone else could as well. The trick consists of using the gesture recognizer to keep track of the starting situation instead of using a variable in our VM. Let’s see how it can be done! The Architecture In a Model-View-ViewModel (MVVM) architecture, we would like for our View to be an exact representation of the data contained in the View Model (VM) . When changes in the VM are discrete, everything works beautifully: if we have a VM with a var name: String and a UILabel in the View to render that name, the MVVM architecture provides an automatic way to update the view when the name changes. However, when things get updated in a continuum, as it happens for the gestures, things can get a little bit messy. In this situation, there are continuous updates to the VM and you may have to work with differential values considering the VM in the previous iteration and the new one. But we don’t have the concept of a previous iteration! In my case, I wanted to move an element on the screen, based on a pan gesture performed by the user. Here are my View Model and the function of the view that layout the elements. The VM contains just a CGPoint that represents an offset, the displacement of the ball from the center of the screen. The layout is performed by setting the center of the ball in the center of the screen, summing it up with the offset property in my VM . To simplify the sum operations, I wrote a straightforward extension for CGPoint : Of course, when the model changes, we want to redraw the screen and move the ball into the eventually new position. This can be done easily with a property observer and an update(...) method in our view: Thanks to this code, whenever the VM is set, the update function is invoked and we instruct UIKit that the View needs to be layout again: in the new layout cycle, the layoutSubviews method will be invoked to redraw the screen. Connecting the View to the VC At this point, we need to implement the gesture and to connect it with our view. To implement a gesture, we need to add a GestureRecognizer. In this specific case, we will use a UIPanGestureRecognizer . The UIPanGestureRecognizer is an object that is able to detect when the user is dragging a finger on the screen, how much are they drag it, and how fast. The pattern to connect a gesture recognizer to an element is the standard Target-Action iOS pattern. Here the code to create a gesture recognizer, assign it to the view, and connect it to the view model: In this snippet, you can see: the declaration of the ball we need to move (line 4) the declaration of the interaction to connect the gesture with the VC (line 7) how to add the ball view to the View (line 10) how to declare a gesture recognizer and how to add it to the view (line 13 and 14) how to handle when the gesture is actually recognized (the method panGestureRecognized at line 17 ) In the panGestureRecognized method, we handle the gesture. Every gesture recognizer has a state variable that tells us in which state of the recognition we are. If we have just detected the gesture, we are in the began state. state. If the user is still dragging, we are in the changed state. state. If the gesture is finished, we could be in the ended state in the canceled state, depending on what the user did. In this method, we can notify the VC that a gesture has been correctly recognized so that it can update the VM accordingly. For sake of completeness, here the VC code that updates the VM : Implementing The Gesture Finally, let’s see how to properly implement gesture recognition. I’ll show the code first, and then we will analyze it together: I added a comment on all the lines to let everyone follow the code with ease. The most interesting chunk is the began block. Here we detect that the interaction has started. What we want is to move the ball from its current position. This is given by the center of the screen plus the current offset, as it is set in the VM . Then, we need to know how much the user dragged the ball with respect to the parent's view. Line 15 does exactly that: it asks the gesture recognizer to retrieve the translation in the parent’s view coordinate system. With those two values, we can compute the new offset from the center, by just summing them up. Then, here the trick: we set this new value as the current translation of the gesture recognizer (line 21) ! If we analyze the GestureRecognizer documentation, in fact, we know that whenever a new gesture is recognized, the gesture recognizer will start the computation from 0 . So, if you are recognizing a translation and you move the ball from the center of the view on the right, the translation will be of (+x, +0) , independently from the previous position of the element. If you are rotating an object, it will always start from 0 , despite you already rotate it before, and so on for each other gesture recognizer. This simple trick, instead, let you set the initial translation, rotation, or zoom so that every other value obtained by the gesture recognizer will be computed with respect to that new initial value instead of 0 . The rest of the snippet is pretty straightforward: we just notify the VC about the translation. Also, after we set the new starting point, implementing the changed and ended state is as trivial as getting the new value and notifying the VC . And this is the result: Note: if you try this code in a playground, the performances would be sluggish. I think that the Playgrounds perform some other operations and they do not render the screen with the same frequency of the simulator. However, a real device or even an iOS simulator will work like a charm. The whole code for this screen ( VC , VM , View ) can be found in this gist. Conclusion Today we have seen how to plug gesture recognition in a MVVM architecture. To achieve a readable and elegant code, we leveraged the setTranslation API to set into the gesture recognizer the initial point for the gesture. All the gesture recognizers have their own version of this API: for example, the UIRotateGestureRecognizer has a setRotation method. Thanks to this trick we are now able to write all our interactions in a very clean way, leveraging what the platform offers, avoiding glitches, and keeping our architecture neat. I am working on iOS for 5 years now, and every week there is some new trick I learn. And this continues to amaze me, every day. And you? What are some tricks that you use and that may be unknown to many others? I would be extremely happy to learn them!

https://medium.com/swlh/gestures-and-mvvm-9f8147b94db1

['Riccardo Cipolleschi']

2020-11-18 11:55:55.454000+00:00

['Mobile App Development', 'Apple', 'iOS', 'UI', 'Swift']

The life of a story

I never understood what writers meant when they said stories take a life of their own. I can string words. Make coherent sentences. Occasionally, coherent paragraphs. But when it comes to writing an entire story, I tend to be a micro-manager. I am governed by details and my immediate perception of reality, most of the time. My stories do not reach their fullest potential. I attended a story slam yesterday. They had a theme, “Fathers”. I was there to support a friend. I came without a story. The evening threatened to end early, I put my name in for Open Mic. I jotted pieces of funny anecdotes and discoveries, cloaked with lightheartedness into my phone. As I stood in front of the crowd, words came flowing, I forgot about my notes. My mind scavenged for the next sentence until it finally got to one that made my throat choked. I looked for more words, it is the only way to stop me crying and suddenly it came, “I am still discovering my dad. Watching him evolving as a person.” I returned to my seat, a little shell-shocked. My neighbour said he liked the vulnerability. I smiled. “It happens.” The story took a life of its own. It dropped the cloak of lightheartedness I had tenderly draped across its shoulders, took me its broad strong arms and showed me what I have always needed to know, I still am my discovering my dad.

https://medium.com/100-naked-words/the-life-of-a-story-f03756e0cb0b

[]

2016-06-27 08:01:01.736000+00:00

['Storytelling', 'Writing', 'Love', 'Writer', 'Fiction']

How to Deal With Chronic Illness and Do Your Job

How to Deal With Chronic Illness and Do Your Job A crash course in employment with mental illness. Photo by Thought Catalog on Unsplash Having a mental or chronic illness and holding down a job can be a challenge. In addition to managing your illness, you manage the aspects of your job and coworkers. For many, this can be incredibly draining. One way to combat this is to put yourself into a routine. I’ve found that when a given task is on an automatic routine, it consumes fewer spoons. The goal is to put as much of your life on routine as possible to reduce spoon consumption. During the workweek, I do my best to go to bed at the same time every night. I find that I fall asleep better and quicker if I do it at the same time every night. If sleep knows where and when to find you, it’ll often come faster. That said, I have an office job that doesn’t take a lot of physical effort and has a regular schedule. Service jobs are much different and require a different approach. If you have a regular schedule than build your sleep schedule around that. Go to bed at the same time before your shifts, even if it means going to bed at 10:30 one night and 8:00 the next. If your shifts are unpredictable but fall within a certain set of hours (daytime business hours, for example), you can wire your sleep patterns around that timeframe with the understanding that some days, you wake up and go straight to work, and other days, you come home from work and go straight to bed. For quite a while, I had two jobs where my schedule was 5 AM-12:30 on Friday and Saturday, 12:30–8:00 PM on Sunday, and 7:00 AM-3:30 on Monday and Tuesday. Whenever I could manage, I went to bed at the same times for the same shifts. This meant that I went to bed at 8:00 p.m. on Thursday and Friday and 1:00 a.m. on Saturday. As for the times outside of work and sleep, I find routines work for me. Eat meals at roughly the same time every day if you can. Make time for yourself to do things that rest and refresh you. Never feel obligated to do social things if you aren’t up for it. For me, social activities are draining, so if I find I have too much on my plate, I try to pare down. Make peace with the fact that something may not get done today, and do your best to get it done tomorrow. At the same time, don’t let yourself descend too far into procrastination. Try to manage your energy in ways that end in a net positive. If you have a good day and have some energy when you get home, tackle the dishes that you’ve been putting off. Alternatively, invest small amounts of energy into doing little bits regularly. Get in the habit of spritzing your shower with cleaner and rinsing it off right after you get done. It will take 30 seconds, but your shower will stay clean out of pure habit. On the opposite end, learn where you can afford to cut corners to conserve energy. If you hate shaving, get an electric razor. If it’s hard to shower, figure out if you can afford to skip a day and invest in dry shampoo. Learn hairstyles that look good but take two minutes. Start minimizing your makeup routine. Keep protein bars around if you aren’t feeling like making breakfast. Put your wardrobe on automatic: I have a dedicated row for each of my clothing items (shirts, pants, etc.) that I cycle through in order. They are all generic enough that everything goes with everything, but because they are in odd numbers, it looks like I picked out my clothes every day. In reality, all I’m doing is pulling the next item in line off of the hanger and putting it on with zero choices on my end. I don’t invest any energy in picking my clothes unless there is a particular thing that I must do which requires a particular clothing choice. On the flip side, find things that give you energy and do them. Develop rituals that are calming and either don’t consume much energy or give you energy and focus. Learn to shave with a straight razor. Take up meditation. Teach yourself to knit. Find a small hobby or thing that puts your mind at rest, even for a little. If you can afford it, go to therapy. There are a number of nonprofits in my town that accept appointments on a sliding fee scale based on income; do a little digging to find a place near you that does this. Medication helps but isn’t for everyone. If you want to but can’t afford it, look into options for insurance, whether through a job, through the Marketplace, or through Medicaid and Medicare. If you are having trouble holding a job, try to find alternative means. There are numerous apps that offer fee-for-service tasks and let you set your own hours, like driving for Uber, Postmates, or Amazon. If you took up a craft, try to find a place to sell what you make, either online or through craft shows. If you need supplemental income, there are a number of legitimate ways to make small amounts of money online, such as Amazon Mechanical Turk. You can self-publish books on Amazon, articles here on Medium, or a number of other places if you’re writing-inclined. There are apps where you can pet-sit or do odd jobs. There are data entry jobs that can be done entirely from home and don’t require a degree. If you have a degree in a particular area, try to turn it into a contract-based gig. People are always looking for freelancers, and the ability to work when you are able can be helpful.

https://medium.com/the-ascent/how-to-deal-with-chronic-illness-and-do-your-job-8d3a246f93d3

['Matthew Maniaci']

2019-09-12 14:12:39.583000+00:00

['Life Lessons', 'Work', 'Self', 'Mental Health', 'Productivity']

Logistic Regression Explained

Logistic Regression Explained [ — Logistic Regression explained simply — ] In this post, I will explain Logistic Regression in simple terms. It could be considered a Logistic Regression for dummies post, however, I’ve never really liked that expression. Before we start, here you have some additional resources to skyrocket your Machine Learning career: Lets get to it and learn it all about Logistic Regression. Logistic Regression Explained for Beginners In the Machine Learning world, Logistic Regression is a kind of parametric classification model, despite having the word ‘regression’ in its name. This means that logistic regression models are models that have a certain fixed number of parameters that depend on the number of input features, and they output categorical prediction, like for example if a plant belongs to a certain species or not. In reality, the theory behind Logistic Regression is very similar to the one from Linear Regression, so if you don’t know what Linear Regression is, take 5 minutes to read this super easy guide: In Logistic Regression, we don’t directly fit a straight line to our data like in linear regression. Instead, we fit a S shaped curve, called Sigmoid, to our observations. Sigmoid function fitted to some data Let's examine this figure closely. First of all, like we said before, Logistic Regression models are classification models; specifically binary classification models (they can only be used to distinguish between 2 different categories — like if a person is obese or not given its weight, or if a house is big or small given its size). This means that our data has two kinds of observations (Category 1 and Category 2 observations) like we can observe in the figure. Note: This is a very simple example of Logistic Regression, in practice much harder problems can be solved using these models, using a wide range of features and not just a single one. Secondly, as we can see, the Y-axis goes from 0 to 1. This is because the sigmoid function always takes as maximum and minimum these two values, and this fits very well our goal of classifying samples in two different categories. By computing the sigmoid function of X (that is a weighted sum of the input features, just like in Linear Regression), we get a probability (between 0 and 1 obviously) of an observation belonging to one of the two categories. The formula for the sigmoid function is the following: If we wanted to predict if a person was obese or not given their weight, we would first compute a weighted sum of their weight (sorry for the lexical redundancy) and then input this into the sigmoid function: 1) Calculate weighted sum of inputs Weighted sum of the input features (feature in this case) 2) Calculate the probability of Obese Use of the sigmoid equation for this calculation Alright, this looks cool and all, but isn’t this meant to be a Machine Learning model? How do we train it? That is a good question. There are multiple ways to train a Logistic Regression model (fit the S shaped line to our data). We can use an iterative optimisation algorithm like Gradient Descent to calculate the parameters of the model (the weights) or we can use probabilistic methods like Maximum likelihood. If you don’t know what any of these are, Gradient Descent was explained in the Linear Regression post, and an explanation of Maximum Likelihood for Machine Learning can be found here: Once we have used one of these methods to train our model, we are ready to make some predictions. Let's see an example of how the process of training a Logistic Regression model and using it to make predictions would go: First, we would collect a Dataset of patients who have and who have not been diagnosed as obese, along with their corresponding weights. After this, we would train our model, to fit our S shape line to the data and obtain the parameters of the model. After training using Maximum Likelihood, we got the following parameters: Parameters and equation of X 3. Now, we are ready to make some predictions: imagine we got two patients; one is 120 kg and one is 60 kg. Let's see what happens when we plug these numbers into the model: Results of using the fitted model to predict obesity given patient weight As we can see, the first patient (60 kg) has a very low probability of being obese, however, the second one (120 kg) has a very high one. Logistic Regression results for the previous examples. In the previous figure, we can see the results given by the Logistic Regression model for the discussed examples. Now, given the weight of any patient, we could calculate their probability of being obese, and give our doctors a quick first round of information! Conclusion and Other resources Logistic regression is one of the most simple Machine Learning models. They are easy to understand, interpretable, and can give pretty good results. The goal of this post was to provide an easy way to understand logistic regression in a non-mathematical manner for people who are not Machine Learning practitioners, so if you want to go deeper, or are looking for a more profound of mathematical explanation, take a look at the following video, it explains very well everything we have mentioned in this post. That is all, I hope you liked the post. Feel free to follow me on Twitter at @jaimezorno. Also, you can take a look at my posts on Data Science and Machine Learning here. Have a good read! For further resources on Machine Learning and Data Science check out the following repository: How to Learn Machine Learning! For career resources (jobs, events, skill tests) go to AIgents.co — A career community for Data Scientists & Machine Learning Engineers. Also, for more posts like this one follow me on Medium, and stay tuned! Also, to go further into Logistic Regression and Machine Learning in general, take a look at the book described in the following article:

https://towardsdatascience.com/logistic-regression-explained-9ee73cede081

['Jaime Zornoza']

2020-11-02 14:28:54.544000+00:00

['Machine Learning', 'Startup', 'Artificial Intelligence', 'Data Science', 'Programming']

Why Do Married Men Watch Porn?

People view porn for a complex number of reasons. · Loneliness — Some unattached men — temporarily or permanently — seek a temporary fantasied partner. Sexual desires fluctuate, and in married couples, those fluctuations aren’t synchronous. Spouses may experience physical or mental problems. If a man travels for work, he will often pull out a webcam to shorten those lonely, long evenings in their hotel rooms. · Relationships — The passionate sex of a new relationship has a shelf life of about one year. Yet, we expect it to endure forever. As it diminishes, we question our sexual competence and find fault with our partners. Relationships are complicated. Sometimes sex is not the primary problem. It may be a symptom of more significant relationship problems. A conflict that has not been addressed may cause withdrawal from sex. That is more common than all the other explanations. Men most typically describe this pattern: Their spouse wishes to go to bed. The male partner says I’ll be up in a bit. I must finish this on my computer. · Self-confidence — Men also sometimes feel they’re not enough. Men avoid sex because of enormous anxiety about it. Men worry about the size of their penises, the firmness of erections, and staying hard. Will I cum too quickly or not be able to cum at all? Am I a lousy lover if my partner doesn’t have an orgasm. Porn can restore some self-confidence, even if it’s all fantasy. Porn is a natural antidote because it is conflict-free. There is no negotiation, no partner’s feelings to consider. You are in control of all the variables. That ideal sexual partner who wants you is one click away. And if tomorrow that ideal completely changes, it’s just another tick. · Anxiety and Boredom — Our minds can’t think of two things at the same time. Sexual fantasies push worries about mortgage payments and job dissatisfaction out of our heads. Masturbation is an excellent way to relieve stress. Sexual fantasies creep into our thinking when the mind is bored or idle. Porn seduces us away from the boredom of ordinary life by its novelty. Porn is a way to escape the discomfort of being where you are. · Fetishes and Kink — Searching a porn site is like walking into a candy store with endless choices. It can create a paralysis of choices. It’s a truism that if something exists, there is porn for it. In the privacy behind their keyboards, people can explore their sexual secrets. They have little fear of real-life consequences. Fetishes are alternative sexual practices that enhance the sexual experience. They are a preference, not a necessity. In a moralistic society, fetishists expect prejudice. They experience it from most of the community, including their spouses. They may be afraid to discuss it for fear their spouse will see their fantasy as sick, deviant, and perverted. The kink that is lacking in long-term relationships is one click away. · Conflicts about sexual orientation — Men in heterosexual relationships with recurring same-sex desires may use porn to act out those fantasies. Men search for gay-male porn in about 5% of their searches. The percentage is even higher in states with a low acceptance of same-sex activity. More men in those states live closeted lives, often married to women. For some, it is a compromise to remain in a mixed-orientation relationship. · Aging — An aging population has high numbers of unattached people. Some turn to porn. As men age, their sexual desire diminishes, and erections become more unpredictable. Porn can help restore sexual vigor and combat anxieties about sexual performance. · Technology — People are spending time on social media and playing video games. But they are also watching porn instead of interacting with each other in the real world. A correlation exists between people having less sex and watching more porn. Correlations do not prove causality. Is technology a cause or an effect of social isolation from cell phones and the internet?

https://medium.com/hello-love/why-do-married-men-watch-porn-2693b1ffeeed

['Loren A Olson Md']

2020-10-26 08:24:32.419000+00:00

['Relationships', 'Self', 'Mental Health', 'Psychology', 'Sexuality']

Will Write For Donuts

Will Write For Donuts Medium’s new compensation system [Update 4/25: This story, about the writers of The Grammar Games searching compensation for their efforts, has become the most popular story in the entire Grammar Games saga. Proving once again that while the pen is mightier than the sword, the donut is mightier than the pen. Look for my self-improvement must-read articles, “You can either be the donut or the hole,” “8 secrets the donut can teach your start up company,” and “I am a donut and this is my story of sexual abuse.”] Update 5/12: Inspired by the quest for donuts, I’ve started a new collaborative book and publication titled “The Tao of Blogging.” Please follow our efforts here: And if you’ve written, or read a really great quote that is humorous or thought provoking, please come to the publication and submit it in the comments section of one of the articles. Thanks!] We, the undersigned cynics, humorists, absurdists, anarchists, and other assorted deviants, have contributed to a new collaborative short but possibly long story called The Grammar Games. What started as a satiric revolt against the overwhelming waves of self-improvement, life hacking, and entrepreneurship articles has meta-morphosed into a symbolic battle against the corporate forces that keep us writers oppressed. Therefore, we will develop a kickstarter program to fund a novel that has given pleasure to tens of… well tens of. Because of the magnitude of the response, we thought “why not reach for the stars?” And so, our campaign will ask the public not to contribute some crappy overbrewed coffee stolen from your nearest twelve-step meeting, but to support the arts with the biggest prize of all… donuts! Show your solidarity! Click to tweet “Will Write For Donuts”

https://medium.com/the-word-is-not-enough/will-write-for-donuts-88f9d4545350

['Lon Shapiro']

2016-05-24 07:31:31.561000+00:00

['Humor', 'Entrepreneurship', 'Writing', 'The Grammar Games']

How Venture Capital Firms Can Diversify — And Mean It

How Venture Capital Firms Can Diversify — And Mean It BX3 Follow Jul 18 · 5 min read by Anne Szustek Talbot, VP of Content, BX3 There’s an adage among journalists, writers, and generally any other creatives who tend to do things with words: write about what you know. While subject-area knowledge certainly helps when writing for, say, a medical drama script team, at the same time, writers and journalists often are better off, both in terms of subject matter and career fulfillment, if they push the boundaries of their knowledge. Consumers Need More Than What’s in Venture Capital’s Usual Scope If the types of startups that tend to receive funding from Silicon Valley venture capital firms are any indication, venture capital firms are hewing to the former aforementioned writer’s adage. The boardrooms of Sand Hill Road are populated with former software engineers. venture capital firms tend to turn out plenty of professed software “solutions.” While the market certainly can stand to benefit from some such products, at the same time, the consumers of the US need more than another project management SaaS. While not necessarily bearing that tag of ESG or SRI, startup funding, if done with a qualitative, holistic view, can be a form of impact investing; with the impact in question being that Silicon Valley holy grail of a buzzword: disruption. Yet, for true disruption and positive impact to happen in entrepreneurship, perhaps we need to disrupt how that funding happens. Disrupting The Disruptors If there were any silver linings to have come out of the COVID-19 pandemic, it’s been the extra time for introspection and examination of our ways of working. Part of this is taking a deeper dive at our supply chains: Why is there such a shortage of testing kits in the US? What is behind our approval process for pharmaceuticals? And, as Elizabeth MacBride, a longtime business and financial journalist and founder of startup publication Times of Entrepreneurship, points out for MIT Technology Review, why hasn’t the venture capital community funded these pharmaceuticals or PPE? Good ideas do get funded; yes. But not unlike a publication that values easy clicks over slow-boil, long-form journalism, venture capital often rewards the types of companies that can scale quickly, preferably to IPO size, meaning fast returns for the venture capital firms that fund them and the institutional investors upstream that are investing in these companies. Often, the companies that meet these requirements are software companies. And, as MacBride’s sources in the article point out, on some level, this venture capital funding goes to the same type of founder. Quoting John Doerr of marquee Silicon Valley VC firm Kleiner Perkins in 2008: many of the top-funded founders “all seem to be white, male nerds who’ve dropped out of Harvard or Stanford and they absolutely have no social life.” Just more than 2 percent of VC money in the US went to female founders in 2017 and 2018, she writes. This study, quoted in Crunchbase in 2019, shows women-founded startups getting 9 percent of investments; black VC-funded founders only accounted for 1 percent of investments. Said Brittany Davis, a black woman who is head of the deal flow team at diversity-centered VC firm Backstage Capital in Crunchbase in 2019, “Even when funds do encounter more diverse founders, they often don’t see the opportunity because either the founder or their business doesn’t fit into their box of what they predict will be successful.” Underpinning The Recovery Diversity in founders makes sense: Rather than some minuscule subset of the US workforce dictating what is relevant enough to society to warrant a $10 million tranche of Series A, many diverse founders’ ideas often come battle-tested in the field, showing their resilience and demand in their target market. One company in the portfolio of LOUD Capital, an early-stage VC headquartered in Columbus, is minority woman-founded SHARE, an on-demand microtransit service that since its launch in 2016, has grown from a local operation in Ohio’s capital city to a service spanning 75 cities across the US. Founded to provide commuting accessibility for thousands of people, many of whom live in smaller communities where public transit coverage may be spotty to non-existent, the startup has expanded its service offerings amid the pandemic to provide delivery services and fulfillment, a lifeline for smaller cities. LOUD has also made recent headlines for the launch of Pride Fund 1, a venture capital fund dedicated expressly for LGBTQ+ entrepreneurs and founders creating funds specifically geared towards the LGBTQ+ community, including potentially a couple of fashion brands, as mentioned in Vogue Business. Under a traditional VC investment rubric, these projects might not pass muster. But in terms of societal relevance, funding has made a positive impact: on a diverse founder, for people who need mobility; and for uninterrupted flow of goods and services. The journalistic thesis statement is there; as is the investment one. Think of it this way: when you read an article that grabs your attention and makes you think, do you recall the statistics underpinning the argument, or are you more likely to remember how someone was directly impacted by those numbers? For example, you might understand that COVID is wreaking an unprecedented economic toll on small business owners and that it’s imperative for communities to support small businesses. But a story on a specific entrepreneur in small-town Virginia and what she’s done to save her small business will imprint this issue in your memory for much longer than a graph or chart ever could. And the impact any such funding will make on this company will have more immediate positive repercussions in this community than another tech startup with a purposely misspelled name. For this reason, it is imperative that if VC actually wants to live up to its often espoused ideals of funding for change, the sector needs to bring on more people that bring the local and industry knowledge and nuance to be sure the startups that stand a chance to serve societal needs get a chance to present, never mind funded, get the due diligence and attention they deserve. Bring in VCs from the South Side of Chicago. Recruit a woman from rural Appalachia and train her in the economic and financial chops needed to assess a new company’s bona fides. Disrupting the status quo is what venture capital purports to be all about. Now let’s see if — quite literally — they can put their money where their mouth is. Originally published at https://www.valuewalk.com on July 18, 2020.

https://medium.com/datadriveninvestor/how-venture-capital-firms-can-diversify-and-mean-it-valuewalk-73fb8c23d98d

[]

2020-07-28 13:04:12.244000+00:00

['Funding', 'Venture Capital', 'Entrepreneurship', 'Diversity', 'Startup']

Is the world flat?

Is Earth really round? Maybe we’re actually living on a pancake-shaped planet? Or perhaps it resembles a triangular prism? These questions form the basis of a debate that has raged on for centuries. Many ancient civilizations subscribed to the belief that Earth is flat. Then science came along and seemingly squashed any notion of this idea — at least, it seemed it did. I recently watched an eye-opening documentary about modern flat-Earth theorists, known as “flat-Earthers”. This growing community of people vehemently defends the concept that the Earth is flat (if that wasn’t obvious enough to you). Does this seem too ridiculous to be true? Then you’ll love this post. As someone who is obsessed with seeking the truth, I was in awe throughout the entire movie. I also couldn’t help but have a ton of questions: Why did these beliefs form? How do they propagate? And what does this mean for the future of humankind? I’ll aim to answer these lofty questions and highlight some of the insights I picked up from the movie in the rest of this post. Do these people actually exist? I honestly had no idea the flat-Earth movement was a thing until recently. It all started one day during lunch with the TruStory team. While gathered around the table, we were discussing and laughing about some of the fun, quirky debates happening on the TruStory app. Out of the blue, one of our team members said, “Let’s hope we never have a flat-Earther trying to debate that the Earth is flat.” That certainly caught my attention — to the point that I almost spit out my food. “Flat-Earthers? What… on Earth is that?” I asked. He chuckled and replied, “People who believe the Earth is flat! You never heard of ‘em?” “Um… no?” I replied. My eyes opened wide at this point. I wasn’t really sure what to make of this. Was this some new fad I was unaware of, like the floss dance or fidget spinners? Was I (gasp) getting old?! My teammate’s eyebrows furrowed. He looked somewhat uncomfortable. “Yeah, well, they exist,” he said in a serious tone. I assumed this meant he didn’t want to get into this topic, so I didn’t press it too much more after this. Instead, I quickly finished up my lunch, saw I had a few minutes to spare before my next meeting, and raced on over to my computer to do some quick Googling about flat-Earthers. After a few curious search queries, I stood there in shock. “Is this real?” I asked myself incredulously. “These people have to be faking it!” From then on, my research completely consumed my thoughts and time. Minutes turned to hours. Hours turned to days. Countless nights passed. The sun rose and set numerous times as the Earth spun around it. OR was the sun spinning around the Earth?! I didn’t know what was right or wrong anymore… the ground felt flat beneath my feet. But then why couldn’t I see past the horizon?! Okay, okay, let’s rewind — I didn’t really spend days researching this. But my Googling did take me down a few rabbit holes. And they left me feeling less and less hopeful for the future of humanity. I had no choice but to figure this thing out. Fortunately, one of these rabbit holes led me to a documentary about the flat-Earth movement called “Behind the Curve”. Of course, I stayed up later that night to watch it. And I’m glad I did. How biases affect our beliefs The movie does an incredible job of documenting the key people behind the movement and how they spread their message. For me, the most fascinating part was trying to comprehend how these people formed these beliefs in the first place. But to understand why this group of people were able to form these beliefs, it’s important to first understand how humans form their beliefs in general. A belief is “an acceptance that a statement is true or that something exists.” Fundamentally, there are two ways to form a belief. One way is to take a set of inputs, study and understand the inputs, and produce an output (i.e., the belief). This is formally known as the “scientific method” — a process for experimentation that is used to explore observations and answer questions. Inputs → Belief The overarching goal of science is to discover cause-and-effect relationships. This is achieved by asking questions, carefully gathering and examining the evidence, and seeing if all the information available can be combined into a logical answer. The other way to form a belief is to first establish the belief and then look for evidence in support of it afterward. In other words, construct a belief and then later try to rationalize it with explanations and supporting evidence. Belief ← Inputs As the writer Michael Sherman says in the scientific journal Nature: As a ‘belief engine’, the brain is always seeking to find meaning in the information that pours into it. Once it has constructed a belief, it rationalizes it with explanations, almost always after the event. The brain thus becomes invested in the beliefs and reinforces them by looking for supporting evidence while blinding itself to anything contrary. Shermer describes this process as “belief-dependent realism” — what we believe determines our reality, not the other way around. Problems arise when thinking like this is unconstrained. Passionate investment in beliefs can lead to intolerance and conflict, as history tragically attests. Shermer gives chilling examples of how dangerous belief can be when it is maintained against all evidence. The flat-Earth theory is the perfect example of this type of belief-forming taken too far. Flat-Earth theorists look out on the horizon and see flat land. They experience flatness when they walk. This gives them the intuition that the world is flat. This belief then gets propagated as widespread truth. But you might be wondering, “What if we just showed them scientific proof that the Earth is not flat?” Well, cognitive bias makes this easier said than done. The dangers of not recognizing your biases There’s an interesting concept known as the Dunning-Kruger effect. In case you don’t know what it means, here’s a quick definition: “A cognitive bias in which people mistakenly assess their cognitive ability as greater than it is. It is related to the cognitive bias of illusory superiority and comes from the inability of people to recognize their lack of ability. Without the self-awareness of metacognition, people cannot objectively evaluate their competence or incompetence. People with substantial, measurable deficits in their knowledge or expertise lack the ability to recognize those deficits and therefore, despite potentially making error after error, tend to think they are performing competently when they are not: ‘In short, those who are incompetent, for lack of a better term, should have little insight into their incompetence — an assertion that has come to be known as the Dunning–Kruger effect.‘” We all have biases. What we think and experience everyday are based on the stories we tell ourselves to explain what’s happening or what has already happened. Stories are how we make sense of the world. For example, last weekend, I was chatting with my boyfriend, and he was recounting our experience at Bikram Yoga that morning. “Man, it was 200-degrees in there. That’s probably why I feel so tired today.” Meanwhile, I was thinking to myself, “Yeah, actually it was like 90 degrees in there. You’re probably tired because you got no sleep last night and drank alcohol, which probably made you dehydrated.” He was telling himself a story to explain how he was feeling. Some of it may have been true, but the rest is mostly rationalization to make sense of his reality. Now, this type of story-telling is completely natural. It’s actually human nature. However, stories are inherently subjective. They are full of biases. When these biases cannot be recognized for what they are — that’s when they become dangerous. In the case of flat-Earthers, they think they know everything there is to know about how the Earth is shaped. Consequently, they disregard any science that disproves this belief. Their lack of ability to recognize this gap in their logic leads them to continue to believe it. Cognitive biases, if not recognized for what they are, eventually turn into propaganda. At this point, you may be wondering, “How does someone ever end up thinking that they know everything there is to know?” After all, some of us here are suffering from the opposite problem: Imposter Syndrome. Well, it usually starts with a lack of trust in conventional wisdom. Some people are educated in such a way that they distrust authority on a regular basis. This spirals inwards on itself and causes a snowball effect to the point that they don’t believe anything. When you don’t trust anyone or anything, you start to form conspiracies to explain different phenomena you’re observing but can’t explain. You latch on to some noise, turn it into data, then call it a fact. I see this sometimes in the Crypto space, unfortunately. People are educated and told not to trust the government. In fact, they’re educated to not trust anything. “Don’t Trust. Verify” is the mantra everyone preaches. As a result, everything is then seen through the lens of “Don’t Trust. Verify.” But even this gets dangerous if taken too far. The point of crypto is NOT to distrust anything a government or centralized entity does. We can’t deny that the government provides useful functions which otherwise could not be purely done by sovereign individuals. If we stopped trusting the government and every centralized entity altogether, we’d likely end up with much bigger problems, such as the tragedy of commons. Taking the “Don’t Trust. Verify” mantra too far could take us off the deep end and lead us to some dark outcomes. It’s okay to be skeptical of the government and centralized entities and seek more efficient ways. It’s not okay to be in complete denial of their usefulness in some regards. There’s a big difference between being skeptical and being in denial. It’s subtle but important: Being skeptical is okay because it usually means you’re willing to find evidence and understand the truth. Being in denial means you’re not willing to accept anything that is contrary to your beliefs. If the beliefs don’t align with reality, those in denial will change reality and not beliefs. This type of close-mindedness is dangerous. It is delusion in its most volatile state. It’s what leads to extreme beliefs like thinking Earth is flat. The key to solving bias? A community of critical thinkers. Do you know what frightens me the most about all of this? It’s not just about flat-Earthers; it’s about the world at large. We’ve got a growing population of people who simply aren’t encouraged to think critically and evaluate expert resources. When human thinking is left to itself, it often gravitates toward prejudice, over-generalization, common fallacies, self-deception, rigidity, and narrowness. [1] We live in a world where we have advanced our understanding of science to a point where we can send humans to the moon. So when you have a group of people who all of a sudden defy all science and go against it, it’s hard not to get frustrated. But getting frustrated or annoyed at people isn’t going to fix the problem. And neither is shaming them. We must develop empathy and see things from their perspective. It’s imperative that we understand where they are stuck and get them unstuck. This means teaching them how to think critically. We must teach people how to acknowledge their own biases so that they can fairly judge both the merits and faults of an idea. But modern social networks don’t incentivize people to think. They incentivize people to consume and react. I believe this is where TruStory is fundamentally different. TruStory is a social network to debate ideas. The community is incentivized to write arguments that convey the merits of their ideas. Others are then encouraged to jump in and find faults in those ideas. This back-and-forth process of debate allows us to flush out our viewpoints and get closer to discovering truths. It’s been amazing to see this community of critical thinkers come together to form a movement. The last thing we want is a world full of people who are easy to manipulate and end up making bad decisions based on flawed logic and thinking. TruStory is our contribution to helping this cause. What about you? This post was originally published here. Join us on TruStory! Subscribe to our YouTube Follow us on Twitter

https://medium.com/trustory-app/is-the-world-flat-635e48d0e4d7

['Preethi Kasireddy']

2019-12-07 00:01:06.067000+00:00

['Debate', 'Social Media', 'Cryptocurrency', 'Psychology', 'Science']

5 Books That Grapple with the Thorny Issue of Genetics and Race

5 Books That Grapple with the Thorny Issue of Genetics and Race These scholars of color combine scientific inquiry and social justice. By Georgia Frances King Though scientists have been studying (and debating) the intersection of race and genetics for decades, the reignition of police brutality protests in the wake of George Floyd and Breonna Taylor’s murders has sparked new interest in old research. Is race genetic? What’s the biological difference between ancestry, ethnicity, and race? What is race-based medicine? What is intergenerational trauma? These aren’t new topics. Whether it’s phrenology or eugenics, there is a long and deeply disturbing history of racism in the field of genetics. Those same inequalities on the patient level — poorer health outcomes, reduced access to care, racial bias in medical data, etc. — persist on the lab level, too. Less than a tenth of STEM workers are Black, and they only make up 3% of physical sciences doctorates. Many put these dismal figures down to discrimination in both the college and job application processes, as well as fewer financial resources. For those who do manage to snag decent research jobs, they are met with prejudice in the field, which just starts the cycle all over again. We wanted to know what the leading scholars of color had to say on the topic, so we decided to put together a short reading list that helps us all better understand the intersection of race, biology, and genetics. Please tweet us more suggestions here! In order to not let the Bunsen burner’s flame go out, the science community needs to continue to care about — and fund — this research long after the media scrum has died down. Book club, anyone? The Fatal Invention: How Science, Politics, and Big Business Re-create Race in the Twenty-first Century by Dorothy Roberts Roberts is a professor of law and sociology at Penn who is a widely read author on the subjects of social justice and the law. In this book, she documents the “invention of race” and warns against classifying race as a biological category. She has also been a big voice in tearing down notions of race-based medicine; here’s her groundbreaking TED talk on it. Her earlier book, Killing the Black Body, specifically focuses on Black maternal mortality and reproductive rights, which have unfortunately gotten worse, not better, since she wrote it 20 years ago. People’s Science: Bodies and Rights on the Stem Cell Frontier by Ruha Benjamin Benjamin is an associate professor in the Department of African American Studies at Princeton and the founder of the Ida B. Wells Just Data Lab. In this book, she puts stem cell research under the microscope to inquire whether it will eradicate or further engrain systemic inequalities. She’s more recently the author of Race After Technology: Abolitionist Tools for the New Jim Code, for which she won the Oliver Cromwell Cox Book Award for anti-racist scholarship. Social By Nature: The Promise and Peril of Sociogenomics by Catherine Bliss Bliss is an associate professor of sociology at Rutgers University who explores the sociology of race, gender, and sexuality in science, medicine, and society. This book explains how both social and genetic factors affect our life outcomes — an interdisciplinary field called sociogenomics — along with the troubling, eugenics-like underpinnings of such ideas. It’s a fresh and insightful look at how the nature vs. nurture debate plays out from a social justice lens. (Her previous book was Race Decoded: The Genomic Fight for Social Justice, if you want even more Bliss.) My Grandmother’s Hands: Racialized Trauma and the Pathway to Mending Our Hearts and Bodies by Resmaa Menakem Menakem is a behavioral health expert who has been a trauma counselor for a diverse group of organizations from Minneapolis Public Schools to the U.S. Armed Forces. This popular and very readable book uses the story of his grandmother as the vehicle to explore the notion of intergenerational trauma and “body supremacy” from the cellular level. A surge of new readers found Menakem’s work in the wake of the most recent Black Lives Matter protests, leading to interviews like this one with Krista Tippett on the popular On Being podcast. Post-Traumatic Slave Syndrome: America’s Legacy of Enduring Injury and Healing by Joy Degruy Degruy is a social worker and mental health researcher who focuses on the intersection of racism and trauma. This seminal book is the culmination of more than 10 years of her research in this space, which explores how African-American families have continued to pass down trauma in a post-Jim Crow world.

https://medium.com/neodotlife/5-books-that-grapple-with-the-thorny-issue-of-genetics-and-race-3d189f85974e

[]

2020-11-26 01:49:12.163000+00:00

['Books', 'BlackLivesMatter', 'Race', 'Science', 'Book Review']

ML-Mania: Progress in Review As a New Decade Dawns

With 2019 forming the end as well as the beginning of a new decade, I have been reviewing the machine learning investments we at La Famiglia have made over the past years. As the turn of the year provides an opportunity for reflection, I have summarised general trends, new frontiers and limitations, as well as three methodologies for framing the commercial potential of machine learning in the wild. I) General Trends A year ago, KDNuggets summarised ML in 2018 as “the year of refinement” with “low hanging fruits having been plucked” and media pushing “overblown fears” of the omnipotence of ML. At the same time, a “reckoning of applied machine learning” took place “as there are just some limits to what we can do with pattern matching alone”. Well, 2019 was something of an elegant albeit non-climatic continuation of these findings: clear progress without a drastic step change. While we have seen a few key advancements in research, such as BERT in NLP (end of 2018, more to follow later), this year was marked by the absence of manifold game-changing breakthroughs and instead presented a phase of maturity and refinement. It seems that ML is now growing up. Macro trends: At a macro level, same as every year: the cost for sensors, compute and networking continues to decrease, building the foundation for ML’s steady commercial progress. AI Chips: A range of companies have achieved key advancements in developing novel chips specialised in AI operations, from architectures optimised for data centres to edge devices, making 2019 a hot year for semiconductors (see Groq announcing the world’s first architecture capable of 1,000,000,000,000,000 operations per second on a single chip/ 250 teraFLOPS (compared to Nvidia x Amazon at 100 teraFLOPS), Intel potentially snapping up Habana Labs for >$1Bn , Graphcore & Microsoft announcing an AI cloud partnership, and Cerebras claiming to have the world’s fastest supercomputer due to a 400,000 core processor). Self-supervised learning: In continuation of advancements in ML research at the end of 2018, 2019 saw the “quiet revolution of semi-supervised learning” , with new progress in semi-supervised learning (alternatively called self-supervised learning) promising to remove the cumbersome bottleneck of labelled data. Through the development of proxy tasks, self-supervised learning enables systems to learn without explicit supervision by learning relevant contextual information instead, thus not requiring pre-existing labeled data. Why is that a big deal? Many companies still stuffer from barriers to automation due to a lack of appropriate data. There are three common barriers to ML automation, starting with a lack of digital data (1st barrier to automation), structured data (2nd barrier to automation), and labelled data (3rd barrier to automation and often the most cumbersome one since scaling labelling efforts remains difficult). Hence, the advent of systems that can be fed on structured digital data alone allures. Due to a range of methodological improvements, self-supervised learning is now hitting its stride. With research teams publishing new methodologies (such as Google’s BERT and Allen Institute’s Elmo) self-supervised learning has had the biggest effect on Natural Language Processing so far, achieving the same performance as supervised learning with a 10x lower amount of training data. It was rolled out on Google in mid-2019, one of the largest changes to search ever, helping to provide more nuance and context in search results. In May 2019, Yann LeCun stated accordingly: “The next AI revolution will not be supervised or purely reinforced. The future is self-supervised learning with massive amounts of data and very large networks.” At the same time, since self-supervised learning also enables scaling with lower amounts of labelled data, together with ever decreasing total costs to run ML in the wild, the next decade promises ML at the edge, ML at scale and ML with less (labelled) data, getting us closer to the paradigm of “ML everywhere” than we might currently anticipate. Exploring sensory frontiers: Ian Goodfellow’s introduction of GANs (Generative adversarial networks — the idea that neural networks contest and thereby improve each other) in 2014 provided a breakthrough in photorealistic image synthesis. In 2018, Deepmind provided more advancement through their work on BigGANs, which essentially scale up GAN models to enhance performance (for a history of GANs, check out this post). This year was marked by further progress of GANs and Variational Auto Encoders (VAE) for audio, image and video synthesis, focusing on first use cases such as fashion model creation for e-commerce sites (e.g. DataGrid), though commercial scale remains low. Overall, through recent advancements, such as machines learning to smell (Google research) and image face generation now being indistinguishable from real photos (see Ian Goodfellow’s comparison), the next decade will further raise questions about the meaning of privacy and authenticity in a sensory world that can be manipulated at the click of a button, while also highlighting unprecedented potential for cost-saving and automation across creative industries. Federated learning: Heralded as a potential breakthrough for machine learning in the previous year, federated learning has disappointed this drastic expectation, yet is also showing promising early application. Federated learning enables ML without direct access to training data — data remains in its location and only computed abstractions are shared with a central model. While providing a method to soothe privacy concerns and more easily process large amounts of data (see e.g. recent news of Nvidia’s use of the technology within hospitals), the commercial reality of federated ML is still marked by key limitations, such as edge device performance and coordination, which is aggravated by a lack of standardised infrastructure and resources on client/edge site, as well as back-tracing of local data. Nevertheless, federated learning is already in production in certain environments that allow access and control over the entire infrastructure, such as Google Keyboard, enabling accurate text predictions and autocorrect without data being shared back to Google (how’s that for win-win?). AutoML: When it comes to AutoML, no big breakthroughs either. AutoML enables computers to automatically generate and test neural networks, thus creating better results than humans would. If leveraged at scale, this could solve a key human bottleneck, and at much lower cost (think about the beauty of ML model generation 24/7 with no breaks needed). Despite commercial releases by Google, the performance of AutoML still lags behind expectations of tech automation hopefuls. While research results are promising, showing that certain tasks can be automated, the key to strong ML performance still lies in the human element (i.e. hyperparameter tuning, architectural and loss function design). “Humans have lots of knowledge that I don’t think AutoML will be able to figure out,” said Quoc Le, lead researcher and creator of AutoML earlier this year. Autonomous driving: There was a hype — and this year it evaporated definitively. Or as a founder in this space put it to me on a more positive note: “2019 has been a wonderful phase of increased realism — so far the kids were playing, now we’ve grown up”. As investment continues to be high, consolidation pressures among autonomous vehicle companies are picking up and new partnerships continue to be announced regularly (e.g. most recently BMW & Daimler). Across the industry, the reality of autonomous driving in the wild lags behind initial expectations: missed launch dates have become the norm and many players struggle to ramp up driven miles. While Waymo remains far ahead of the curve and Tesla works hard to show the world new form factors as well as its superior data collection and algorithmic capabilities, putting out a bold vision of enabling L5 without Lidar sensors, in 2019 the world agreed that L5 autonomous cars in mega cities remain far in the future. Still, we anticipate that other use cases in more structured and controlled environments (trucking lanes, warehouses, etc.) will provide promising business cases in the next few years. Tooling: Great news for productivity junkies: On the tooling front, steady progress has been made, with a range of tools now making the work of engineers and data scientists more productive (see here for an overview). Talent: As sought after as ever, ML talent remains a rare good that is worth fighting for, though Europe still is nowhere close to winning the battle. In 2019, a report from the Centre for Data Innovation concluded that the United States is leading in AI, followed by China and then the EU. While the US and China each lead in several categories (talent, development, hardware, research vs. adoption and data, respectively), the EU does not achieve any category leadership (oy gevalt!). Already frequently lamented by politicians and business professionals, I believe the next decade will escalate tensions in the race to AI supremacy, with Europe’s wish to be at the forefront remaining as vulnerable as ever. However, with the topic of ethics and governance becoming more important, as shown by several research initiatives across European universities (e.g. Facebook & TU Munich, Stephen Schwarzman’s historical $188M donation to the University of Oxford; both for the purpose of funding research about ethics in AI) the scales might soon tip more into Europe’s favour again. II) Method I of III: Categorising the Potential of Automation To help provide structure in discussing the potential of data and ML for automation, delineating areas in which humans vs. machines excel is key. While a lot of the public discourse focuses on AI totalitarianism, predicting drastic takeovers from machines and robots in all walks of life, the reality of how automation is embedded into our work and private lives is more nuanced. Depending on how well processes are defined, the availability of structured and labelled data, as well as ability to provide production-ready products, form important prerequisites for machine automation potential (note that automation can be driven by ML, but also the orchestration of digital workflows alone, which often provides much lower hanging fruits). As reported by MMC Ventures in 2019, 1600 AI startups call Europe home. Most of them focus on the verticals of health, fintech, and media, as well as the business functions of marketing, BI & analytics. When assessing the ability of machines to take an ever bigger role in our daily lives, it is worth considering the strength of human capabilities versus the readiness of automation. As the graph below depicts, the potential for automation can be categorised alongside a theoretical productive balance between humans and machines, with further productivity pathways delineating human as well as machine prevalence. Based on three such theoretical productivity lines, four fields emerge: The Field of Tooling: In this area, human capabilities remain far superior to machines. Humans use machines as a mere tools that have little to no influence on the quality of the output. In this field, machine impact is low, and human impact high. Examples would be software tools for writing (i.e. a best-seller will not be decided by using Word or Pages), or creating a musical masterpiece. In this area, human capabilities remain far superior to machines. Humans use machines as a mere tools that have little to no influence on the quality of the output. In this field, machine impact is low, and human impact high. Examples would be software tools for writing (i.e. a best-seller will not be decided by using Word or Pages), or creating a musical masterpiece. The Field of Assistance: In this area, the human is assisted by a machine. Machine impact is medium because the human in the loop still crucial to the final output (e.g. managing a sales relationship). Here, machine impact is low to medium and human input is important. Examples include voice and text assistants, chatbots, L3 autonomous driving. We count portfolio companies like Affinity (ML-enabled CRM) and Impira (ML-enabled asset management system) into this category. In this area, the human is assisted by a machine. Machine impact is medium because the human in the loop still crucial to the final output (e.g. managing a sales relationship). Here, machine impact is low to medium and human input is important. Examples include voice and text assistants, chatbots, L3 autonomous driving. We count portfolio companies like Affinity (ML-enabled CRM) and Impira (ML-enabled asset management system) into this category. The Field of Augmentation: In this field, the capabilities of machines exceed those of humans, enabling humans to do things much more effectively. Humans are still needed as a final control layer, but not crucial to overall quality of the output, which is mainly driven by machine performance. Here, machine impact is medium to high, whereas human impact is low but still necessary for seamless operations or near-perfect results. Examples include product recommendations, state of the art OCR functionality, predictive maintenance, L4 autonomy, and production optimisation platforms. We count companies like Fox Robotics (automated forklifts), Omnius (streamlined workflows for insurances), Alcemy (cement optimisation platform), and BigFinite (manufacturing optimisation for the process industry) into this category. In this field, the capabilities of machines exceed those of humans, enabling humans to do things much more effectively. Humans are still needed as a final control layer, but not crucial to overall quality of the output, which is mainly driven by machine performance. Here, machine impact is medium to high, whereas human impact is low but still necessary for seamless operations or near-perfect results. Examples include product recommendations, state of the art OCR functionality, predictive maintenance, L4 autonomy, and production optimisation platforms. We count companies like Fox Robotics (automated forklifts), Omnius (streamlined workflows for insurances), Alcemy (cement optimisation platform), and BigFinite (manufacturing optimisation for the process industry) into this category. The Field of Automation: In this field, machines have achieved prevalence: Human input is near obsolete — human work can be fully automated, with machines often achieving results far superior to human capabilities. In this field, machine impact is high and human impact low to nonexistent. Examples include fraud and cancer detection, image/video-based quality control, as well as specialised manufacturing processes. In our portfolio, we count companies like Osaro (automated picking and assembly) and CloudNC (autonomous machining) into this category. At La Famiglia, we believe big businesses can be built across all four categories, albeit scalability concerns exist for the tooling space, as well as potential price pressure in the field of automation for low-complexity tasks, as has already happened across API-based business models. In 2019, the fields of assistance and enablement got us most excited, since this is where great products make a difference to human workflows (the famous 10x), providing clever yet often simple ways for both to work together seamlessly. Moreover, the two areas cannot be fully separated, with many platforms showing characteristics of both areas (e.g. an ML-enabled CRM like Affinity providing augmentation through streamlined relationship information, yet still requiring the human in the loop for key relationship management). Looking at the next year, we will continue our hunt for companies tackling complex automation through best-in-class tech teams, as well as augmentation and assistance through companies that understand how to create 10x impact through streamlined workflows and superior analytical insights. III) Method II of III: Dress to Impress But Better Low-ball for Success: Anticipating Human Expectation To evaluate why some products have underwhelmed rather than overwhelmed on the automation expectation scale, examining human expectation is key. Primed by darwinistic survival instinct, negative events impact humans more strongly than positive events of the same magnitude (the negative feeling of losing $1 weighs more strongly than the happy feeling of gaining $1). As the scale of measuring automation success is not one-dimensional, but often impacted by at least two aspects (overall quality & overall cost) this Negativity Bias has resulted in certain products remaining below expectation levels of the past decade. The status quo being the point of reference for assessments of new automation products, machine translation, despite strong progress not being perfect yet, has found wide adoption since the expectation level for many languages was no or only very expensive translation — making even patchy translation a strong improvement. On the other hand, interactions with voice assistants and chatbots continue to underwhelm customers. Rarely able to move beyond simple interactions, when comparing human-to-machine with human-to-human conversation, a clear gap to the status quo remains, driven by a lack of meaningful interactivity. To examine ML’s past and future potential, we hence always ask ourselves whether ML-driven automation features of a product will delight and raise the bar, rather than underwhelm and annoy in comparison to the status quo, despite potentially promising other optimisation criteria, e.g. potential to decrease overall cost. IV) Method III of III: Understanding What Moves the Needle of Your Business — Where Is the Money? While I felt that AI-bullshit bingo has decreased in 2019, we still saw a range of companies this year that utilised AI and ML as a buzzword to jazz up their deck, rather than a technology that can drive meaningful value for their customers, i.e. help solve their problems. When determining if and how ML can add meaningful value to businesses, we find it helpful to separate three categories. Scale: Will the business benefit from driving higher scale through automation (100x more items processed, no need to rest)? E.g. generation of additional business where operational capacity is a key bottleneck (e.g. in labour-constrained markets); alleviating cost pressure in stagnating or declining businesses Will the business benefit from driving higher scale through automation (100x more items processed, no need to rest)? E.g. generation of additional business where operational capacity is a key bottleneck (e.g. in labour-constrained markets); alleviating cost pressure in stagnating or declining businesses Quality: Can ML achieve better results than humans could? E.g. driving better quality in high-value and high-risk environments, such as cybersecurity or health. Important note: often the combination of ML and humans achieve best quality (i.e. humans providing context to pre-analysed ML results) Can ML achieve better results than humans could? E.g. driving better quality in high-value and high-risk environments, such as cybersecurity or health. Important note: often the combination of ML and humans achieve best quality (i.e. humans providing context to pre-analysed ML results) Time: Often, ML can achieve results much faster than humans by quickly sorting through thousands of possible options. Does moving closer to real-time functionality actually add value to clients though? E.g. ML enabling servicing clients faster, thus generating higher customer happiness and driving retention Good founders will have thought about the underlying business need of their clients, knowing exactly why automation features make sense and drive value. V) Outlook What will the 2020s hold? The 2010s have been the decade of unmet expectations on both ends of the innovation bullishness scale, disappointing harsh critics and strong enthusiasts alike. Coming after decade that moved from cries of “all hail the almighty algorithm” and computers beating humans in a range of complex tasks to an awakenings across the board, including chatbots still being shitty and the far away reality of fully autonomous vehicles, I believe the 2020s will move us into a world in which human-machine interaction becomes the de-facto status quo everywhere. Pioneers will achieve significant levels of advanced automation in select areas (e.g. warehousing), and even laggards will steadily exploit assistance and augmentation opportunities. All in all, while the robots aren’t coming for us (yet), I look back at the past decade with a sense of deep serenity over the fact that novels won’t be written by computers any time soon. This serenity is met by excitement in the wake of a new age of automation and the benefits this would entail if executed correctly, yet also staggering unease in light of many societal challenges that will arise. Products built by empathetic and purpose-driven founders will likely provide some answers — and even more new questions. So onto more golden ML years! (Recommended Reads for ML research / investment overviews in 2019: Thanks to great ML startups https://luminovo.ai/ & https://recogni.com for your valuable feedback on writing this review!

https://medium.com/swlh/ml-mania-progress-in-review-as-a-new-decade-dawns-56e493d895d8

['Judith Dada']

2019-12-09 20:12:54.933000+00:00

['Machine Learning', 'Artificial Intelligence', 'Automation', 'Venture Capital', 'Entrepreneurship']

Draw your problem

Draw your problem Your hand, a pen and some paper are your greatest problem-solving tools When I get stuck on something, a problem I can’t figure out how to solve, I tend to do things like ruminate on the problem, write down some words about it, have a [talking] meeting about it, maybe go for a walk in nature. I expect that with enough dedicated thought, I’ll figure things out. I forget (again and again!) that one of the best tools available to me is drawing. Drawing benefits the brain in many ways, according to Cara Bean’s cute illustrated ‘Why Draw?’ booklet: Drawing can instigate the development of critical thinking and problem-solving . . The act of drawing can stimulate positive brain chemistry like serotonin, endorphins, dopamine, and norepinephrine. like serotonin, endorphins, dopamine, and norepinephrine. Drawing can reduce stress . . (references) So drawing can reduce the stress of feeling stuck, help you get unstuck, and make you feel happier. I know this, so why do I keep forgetting to draw my problems? (I think the answer is this: too much screen time keeps me overly focused on using technology to address my problems.) It happened to me just this week. As I’ve been starting up Pictal Health, a company to help patients visualize their health histories, I’ve been feeling all of the pain, imposter syndrome, and overall discomfort that goes along with starting something outside of my comfort zone. I’m a designer who likes to solve problems and make things, and I’ve felt blocked about how to approach business models, sales strategies, and things of that nature. I was spinning out, ruminating in circles, thinking that maybe I should do something else with my life, when I decided to draw my problem. I’ll come back to that in just a minute, along with some other problem-drawing examples. But first… How do you draw your problem? First, you don’t have to be an ‘artist’ to draw your problems. And you don’t have to even draw a picture — writing words down on a blank piece of paper can help. Just put pen to paper. If you want, start with some simple lists. For example, ‘things that are blocking me.’ Or the classic ‘pros & cons’ list: Or what about a simple table? A table or matrix can be really helpful when you’re trying to compare multiple facets of the same items. A classic example is a scorecard. Let’s say you’re scoring different pieces of software. How do the different options compare on price, customer service, and usability? Often we use a spreadsheet for tables, which makes sense in many cases, but hand-drawn tables can also be interesting (as you’ll see.) You could also start to loosely map out relationships between things — this is helpful when you’re trying to make sense of how different entities (like departments, teams, etc.) relate. This is called a mind map or ‘ecosystem diagram,’ and these things can get pretty involved! A nested bubble diagram, as shown below, can be a nice, quick, sketchy way to represent categories with sub-items or sub-categories. Of course you could use lists for something like this too, but I find something satisfying about the bubbles, and you can use them to represent size or importance if you want. When you’re trying to sort out upcoming events, a timeline can be a very effective, calming tool. (I’ve written about the value of ‘sketchy timelines’ in the past.) Somehow, when you can see everything that’s coming up, it’s more manageable. There are a lot of ways to draw time, and below is one type of timeline that shows discrete events — I usually keep a version of this on my refrigerator at all times to show upcoming events and travel. You can show phases of time using a simple gantt chart format; this is a common need for interdisciplinary teams who need to coordinate their work. There are plenty of project management tools that you can use to create detailed gantt charts, but it’s also nice to take a very first pass by hand to kick off your thinking. I often will use some kind of rough flow diagram to help me understand what needs to happen in what order. So, these are just a few methods and diagrams I like to use to sketch out problems. It can and should be ugly. The above examples are misleadingly tidy; drawing your problem doesn’t need to be pretty, and it doesn’t have to make sense to anyone but you. At this stage, you’re just writing words down and drawing shapes in an attempt to create some meaning out of that jumble of thoughts that’s smashing around in your big, smart brain. It’s pre-work, basically; sketching out a general framework that you can then turn into something more polished — for example an article, an agenda, an itinerary or work plan, a proposal…you get the idea. Off-screen is best. I’m partial to using large pieces of 11x17 paper to draw out my problems. A whiteboard is also nice. Any format that enables you to represent ideas ‘in real life’ and at large scale will give you the space to explore them differently than you could if you were constrained by a specific screen size. And, drawing on paper gives your eyes and mind a much-needed break from your screens. I like to keep a stack of paper on the side of my desk at all times, so I can grab one and start drawing when needed. All that said, I have often used a tablet to draw out ideas and illustrations (including many of those in this article.) So that’s a legitimate option.

https://medium.com/pictal-health/draw-your-problem-5afffa5fdf5f

['Katie Mccurdy']

2019-12-06 15:06:56.390000+00:00

['Startup', 'Design', 'Problem Solving', 'Drawing', 'Visual Thinking']

Streamlit vs. Dash vs. Shiny vs. Voila vs. Flask vs. Jupyter

Streamlit vs. Dash vs. Shiny vs. Voila vs. Flask vs. Jupyter Comparing data dashboarding tools and frameworks Source: Author Over the last three years, Dash and Streamlit have surged in popularity as all-in-one dashboarding solutions. Source: Author Data dashboards — Tooling and libraries Nearly every company is sitting on valuable data that internal teams need to access and analyze. Non-technical teams often request tooling to make this easier. Instead of having to poke a data scientist for every request, these teams want dynamic dashboards where they can easily run queries and see custom, interactive visualizations. Data dashboards can make data more accessible to your non-technical teams. Source: Author A data dashboard consists of many different components. It needs to: Analyze: Manipulate and summarize data using a backend library such as Pandas. Manipulate and summarize data using a backend library such as Pandas. Visualize: Create plots and graphs of the data using a graphing library such as Bokeh. Create plots and graphs of the data using a graphing library such as Bokeh. Interact: Accept user input using a frontend library such as React. Accept user input using a frontend library such as React. Serve: Listen for user requests and return webpages using a web server such as Flask. In the past, you’d have had to waste a significant amount of time writing all the “glue” code to join these components together. But with newer libraries like Streamlit and Dash, these components come in a single package. Still, figuring out which library to use can be challenging. Here’s how they compare as well as some guidance on how to choose which one is best for your project. [Do you want more detailed tooling comparisons that cut through the marketing-speak? Sign up to our weekly newsletter.] Just tell me which one to use As always, “it depends” — but if you’re looking for a quick answer, you should probably use: Dash if you already use Python for your analytics and you want to build production-ready data dashboards for a larger company. if you already use Python for your analytics and you want to build production-ready data dashboards for a larger company. Streamlit if you already use Python for your analytics and you want to get a prototype of your dashboard up and running as quickly as possible. if you already use Python for your analytics and you want to get a prototype of your dashboard up and running as quickly as possible. Shiny if you already use R for your analytics and you want to make the results more accessible to non-technical teams. if you already use R for your analytics and you want to make the results more accessible to non-technical teams. Jupyter if your team is very technical and doesn’t mind installing and running developer tools to view analytics. if your team is very technical and doesn’t mind installing and running developer tools to view analytics. Voila if you already have Jupyter Notebooks and you want to make them accessible to non-technical teams. if you already have Jupyter Notebooks and you want to make them accessible to non-technical teams. Flask if you want to build your own solution from the ground up. Quick overview Not all the libraries are directly comparable. For example, Dash is built on top of Flask, and Flask is a more general framework for web application development. Similarly, each library focuses on a slightly different area. Streamlit and Dash are full dashboarding solutions, focused on Python-based data analytics and running on the Tornado and Flask web frameworks, respectively. and are full dashboarding solutions, focused on Python-based data analytics and running on the and web frameworks, respectively. Shiny is a full dashboarding solution focused on data analytics with R. is a full dashboarding solution focused on data analytics with R. Jupyter is a notebook that data scientists use to analyze and manipulate data. You can also use it to visualize data. is a notebook that data scientists use to analyze and manipulate data. You can also use it to visualize data. Voila is a library that turns individual Jupyter notebooks into interactive web pages. is a library that turns individual Jupyter notebooks into interactive web pages. Flask is a Python web framework for building websites and apps — not necessarily with a data science focus. Some of these libraries have been around for a while, and some are brand new. Some are more rigid, and have their own structure, while others are flexible and can adapt to yours. Some focus on specific languages. Here’s a table showing the tradeoffs: Source: Author We’ve compared these libraries on: Maturity: Based on the age of the project and how stable it is. Based on the age of the project and how stable it is. Popularity: Based on adoption and GitHub stars. Based on adoption and GitHub stars. Simplicity: Based on how easy it is to get started using the library. Based on how easy it is to get started using the library. Adaptability: Based on how flexible and opinionated the library is. Based on how flexible and opinionated the library is. Focus: Based on what problem the library solves. Based on what problem the library solves. Language support: The main languages the library supports. These are not rigorous or scientific benchmarks, but they’re intended to give you a quick overview of how the tools overlap and how they differ from each other. For more details, see the head-to-head comparison below. Streamlit vs. Dash Streamlit and Dash are the two most similar libraries in this set. They are both full dashboarding solutions built with Python, and both include components for data analysis, visualization, user interaction, and serving. Although they’re both open source, Dash is more focused on the enterprise market and doesn’t include all the features (such as job queues) in the open source version. By contrast, Streamlit is fully open source. Streamlit is more structured and focused more on simplicity. It only supports Python-based data analysis and has a limited set of widgets (for example, sliders) to choose from. Dash is more adaptable. Although it’s built with Python and pushes users towards its own plotting library (Plotly), it’s also compatible with other plotting libraries and even other languages, such as R or Julia. Use Streamlit if you want to get going as quickly possible and don’t have strong opinions or many custom requirements. if you want to get going as quickly possible and don’t have strong opinions or many custom requirements. Use Dash if you need something more flexible and mature, and you don’t mind spending the extra engineering time. Streamlit vs. Shiny Streamlit is a dashboard tool based on Python, while Shiny uses R. Both tools focus on turning data analysis scripts into full, interactive web applications. Because Python is a general-purpose language while R is focused solely on data analytics, the web applications you build with Streamlit (based on the Tornado web server) are more powerful and easier to scale to production environments than those built with Shiny. Shiny integrates well with plotting libraries in the R ecosystem, such as ggplot2, while Streamlit integrates with Python plotting libraries such as Bokeh or Altair. Use Shiny if you prefer doing data analysis in R and have already invested in the R ecosystem. if you prefer doing data analysis in R and have already invested in the R ecosystem. Otherwise use Streamlit (or Dash — see above). Streamlit vs. Voila Streamlit is a complete data dashboarding solution, while Voila is a simpler and more limited tool that lets you convert existing Jupyter Notebooks into basic data dashboards and serve them as web applications to non-technical users. Like Streamlit, Voila is built on top of the Tornado web framework, so you can use Jupyter notebooks along with Voila to get something broadly similar to Streamlit. But Streamlit is more flexible (it doesn’t require you to use Jupyter), while Voila can be simpler (provided you already have Jupyter Notebooks you want to present). Voila uses Jupyter’s widget library, while Streamlit uses custom widgets — so if you’re already familiar with Jupyter, you’ll find Voila easier to work with. Use Streamlit If you’re looking for an all-in-one solution. If you’re looking for an all-in-one solution. Use Voila if you already have Jupyter Notebooks and are looking for a way to serve them. Streamlit vs. Jupyter Notebooks Streamlit is a full data dashboarding solution, while Jupyter Notebooks are primarily useful to engineers who want to develop software and visualizations. Engineers use Streamlit to build dashboards for non-technical users, and they use Jupyter Notebooks to develop code and share it with other engineers. Combined with add-ons such as Voila, Jupyter Notebooks can be used similarly to Streamlit, but data dashboarding is not their core goal. Use Streamlit if you need dashboards that non-technical people can use. if you need dashboards that non-technical people can use. ‍Jupyter Notebooks are best if your team is mainly technical and you care more about functionality than aesthetics. Streamlit vs. Flask Streamlit is a data dashboarding tool, while Flask is a web framework. Serving pages to users is an important but small component of data dashboards. Flask doesn’t have any data visualization, manipulation, or analytical capabilities (though since it’s a general Python library, it can work well with other libraries that perform these tasks). Streamlit is an all-in-one tool that encompases web serving as well as data analysis. Use Streamlit if you want a structured data dashboard with many of the components you’ll need already included. Use Streamlit if you want to build a data dashboard with common components and don’t want to reinvent the wheel. if you want a structured data dashboard with many of the components you’ll need already included. Use Streamlit if you want to build a data dashboard with common components and don’t want to reinvent the wheel. Use Flask if you want to build a highly customized solution from the ground up and you have the engineering capacity. Dash vs. Shiny Dash and Shiny are both complete data dashboarding tools, but Dash lives mainly in the Python ecosystem, while Shiny is exclusive to R. Dash has more features than Shiny, especially in its enterprise version, and it’s more flexible. Python is a general-purpose programming language, while R is focused solely on data analytics. Some data scientists prefer R for its mature libraries and (often) more concise code. Engineers usually prefer Python, since it conforms more closely to other languages. Use Dash if your team prefers Python. if your team prefers Python. Use Shiny if your team prefers R. Dash vs. Voila and Jupyter Notebooks Dash is an all-in-one dashboarding solution, while Voila can be combined with Jupyter Notebooks to get similar results. Dash is more powerful and flexible, and it’s built specifically for creating data dashboards, while Voila is a thin layer built on top of Jupyter Notebooks to convert them into stand-alone web applications. Use Dash if you want to build a scalable, flexible data dashboarding tool. if you want to build a scalable, flexible data dashboarding tool. Use Voila if you have existing Jupyter Notebooks you want your non-technical teams to be able to use. Dash vs. Flask Dash is built on top of Flask and uses Flask as its web routing component, so it’s not very meaningful to compare them head-to-head. Dash is a data dashboarding tool, while Flask is a minimalist, generic web framework. Flask has no data analytics tools included, although it can work with other Python libraries that do analytics. Use Dash if you want to build a data dashboard. if you want to build a data dashboard. Use Flask if you want to build a far more generic web application and to choose every component in it. Shiny vs. Voila + Jupyter Notebooks Shiny is a data dashboarding solution for R. While you can use Voila and Jupyter Notebooks with R, these are tools that focus primarily on the Python ecosystem. Use Shiny if you already do your data analytics in R. if you already do your data analytics in R. Use Voila if you already have Jupyter Notebooks you want to make more accessible. Shiny vs. Flask Shiny is a data dashboarding tool built in R. Flask is a web framework built in Python. Shiny works well with R plotting libraries, such as ggplot2. Flask doesn’t have any data analysis tools built in by default. Use Shiny if you’re building a data dashboard and you want to do your data analysis with R. if you’re building a data dashboard and you want to do your data analysis with R. Use Flask if you want to build a generic web application from the ground up. Voila vs. Flask Voila is a library to convert Jupyter Notebooks to stand-alone web applications and serve them using Tornado. Like Tornado, Flask is a generic web framework. While it would be possible to use Flask to serve Jupyter Notebooks, you would have to reimplement most of the Voila library — so unless you have a very specific reason, it’s better to simply use Voila. Final remarks All the tools we’ve covered here can help you access the value locked away in your existing data. One common mistake we see teams make is getting too tied up in choosing which tools to use, rather than focusing on the data itself. While using the wrong tools can definitely hinder your analysis, it’s more common for teams to get bogged down by so-called Bikeshedding: spending too much time debating details that aren’t very important. If you’d like to chat about exploring your data and turning it into more revenue, book a free call with our CEO.

https://towardsdatascience.com/streamlit-vs-dash-vs-shiny-vs-voila-vs-flask-vs-jupyter-24739ab5d569

['Markus Schmitt']

2020-10-08 13:56:56.540000+00:00

['Machine Learning', 'Jupyter Notebook', 'Big Data', 'Streamlit', 'Data Science']

Emily Hicks

Emily Hicks President and Co-Founder, FREDsense Emily Hicks is President of FREDsense, a Calgary, Canada based biotechnology startup focused on the measurement of water quality. Emily co-founded the company with CEO David Lloyd in 2013. FRED stands for Field Ready Electrochemical Detector, which is the product that Emily — along with her FREDsense colleagues — invented, developed and brought to market. It’s used to detect trace amounts of chemicals in a water using a groundbreaking new approach using biologically engineered bacteria. Her studies in biomedical sciences at the U of C eventually led her to work on the technology on which FREDsense is based. She is a named inventor in the 2013 patent related to that work. Amongst her wide variety of accolades, Emily has been selected as a Kairos Society Fellow, one of the Top 30 under 30 in sustainability in Canada, a National Nicol Award winner in 2014, the Parlee McLaws Females in Energy Scholorship, amongst many other awards. Emily Hicks is a passionate scientist and entrepreneur. In our wide ranging interview, she not only eloquently explains the FREDsense technology in terms we can all understand but also the pleasures and pitfalls of the entrepreneurial life. It’s a candid discussion for which the answer to at least some of the questions will come as a surprise to our listeners. Our interview with Emily was recorded live at the INVENTURE$ conference in Calgary, in June of 2018.

https://medium.com/the-worknotwork-show/emily-hicks-5c3196bd14d2

['Terence C. Gannon']

2019-03-23 01:44:19.121000+00:00

['Biotechnology', 'Startup', 'Podcast', 'Interview', 'Water']

12 Steps For Beginner To Pro In Data Science In 12 Months!

The 12 Ultimate Steps to Follow over the course of the year — Beginners: 1. Learning Programming Programming is the heart of Data Science. It is essential to have some knowledge of programming to succeed as a data scientist. Coding and programming knowledge is almost a compulsory requirement to have an in-depth understanding of the field of data science. Even if you lack the coding or programming skills, but you have to interest to learn and pursue these techniques, then this should not be a major concern. In my opinion, the two main languages you should know to do well in the field of Data Science in Python and SQL. The reason I have suggested these two languages is because Python is a fantastic starting choice for most beginner-level programmers, even for people with no coding experience. Hence, it is probably the best starting point because of its simplicity. Structured Query Language (SQL) is a domain-specific language used in programming and designed for managing data held in a relational database management system (RDBMS), or for stream processing in a relational data stream management system (RDSMS). It is particularly useful in handling structured data, i.e. data incorporating relations among entities and variables. SQL will play a great role in analyzing the various data that you will gather while working in Data Science. It will help you to create systematic arrangements to solve complex data related queries. It also helps you to maintain and manage the huge amount of data that you will eventually be dealing with. I have spoken about Python in most of my articles and have immensely praised its versatility and simplicity in the field of data science. I will make sure I write an article covering the complete beginners guide to Python next year to help you all in understanding some basic concepts better. You can check out the bonus section for more information related to Python. Bonus: This Section will involve parts that I have discussed previously in my other articles. However, it is extremely beneficial for beginners, and would recommend giving it a read for the new viewers. If you already read this, feel free to skip ahead to the next step. Python is an object-oriented, high-level programming language that was released way back in 1991. Python is highly interpretable and efficient. Python is versatile, and thanks to its resourcefulness, it is a suitable fit for Data Science. I initially started with languages like C, C++, and Java. When I finally encountered Python, I found it to be quite elegant, simple to learn, and easy to use. Python is the best way for anyone, even people with no prior experience with programming or coding languages, to get started with machine learning. Despite having some flaws, like being considered a “slow” language, Python is still one of the best languages for AI and machine learning. Although there are a variety of other languages such as Julia, Golang, etc., which might be quite competitive against Python in the future years, the latter remains the better choice at this point. The main reasons for the popularity of Python for Data Science despite other languages like R is as follows — As mentioned previously, Python is a simple language and is overall consistent. The rapid increase in popularity in comparison to other programming languages makes it a suitable pick for beginner-level programmers. Has extensive resources concerning a wide range of libraries and frameworks for supporting Data Science. Versatility and platform independence, which means Python can import essential modules built in other programming languages as well. It has a great community with continuous updates. The Python community, in general, is filled with amazing people, with constant updates made to improve Python. To get started with Python, you can download it from here. Understanding the basics of the Python programming language is undoubtedly the most important aspect to master Python. There are many key concepts like keywords and identifiers, variables, iterative statements like “for” loop, “while” loop, the comment lines, control statements, and so much more. We will cover all this extensively in a future article! 2. Understand Math If programming is the heart of Data Science, then Math is the brain! Mathematics, I find, is one of those subjects you either learn to love or end up loving to hate. Some find math as an amazing subject while others find all these number’s thing kind of boring. It does not matter which side of the spectrum you are on because math is, fortunately, or unfortunately, one of the most fundamental requirements for machine learning and data science. Mathematics is an essential requirement for data science. Linear algebra, calculus, probability, and statistics are the most significant concepts that you need to know in order to conquer all the mathematical aspects of data science. A high school understanding of the basics of these concepts would suffice for a beginner to enter into the universe of data science. However, if you are not too confident with these concepts or need a brief brushing, then I would highly recommend checking out reading some articles on TDS because they explain most concepts with simplicity and ease. YouTube videos are also a great alternative option to learn these concepts. Mathematics is required for building predictive machine learning models, understanding probabilistic and deterministic approaches to solving Bayesian and other similar problems, understanding backpropagation in deep neural networks, analyzing gradient descent, and so much more. If you are interested in learning mathematics from scratch, below are some references that you might useful. Useful Resources To Consider: 1. Khan Academy: Best place for you to start off with learning basic mathematical concepts like linear algebra, calculus, and probability and statistics. 2. 3Blue1Brown: One of the best YouTube channels to check out some brilliant in-depth explanations and intuitively understand concepts much better. 3. Books: If you are more into reading books, then do a quick Google search to check out some outstanding resources for the best books to learn Mathematics. You should prefer separate books for each specific topic for better practice. 3. Intuitive Understanding Of Basic Concepts Develop an intuition of the concepts. Don’t mug up! The subject of Data Science is a humongous field, and there are tons of theoretical aspects to be understood by beginners of the field. It is completely alright to take your time studying the concepts by developing a strong intuitive as well as a practical understanding. Since you are now in the third step, you will probably have a decent understanding of the Python programming language and the math required for machine learning. Try to implement various math concepts such as Euclidian distance and similar concepts in Python from scratch without utilizing any machine learning libraries. Even if it is just a simple Machine learning algorithm, I would highly recommend not to use the scikit-learn library or similar helpful tools for easier implementations. Instead, try to detect the best possibilities and execute them from scratch on your own. This helps to improve skills and gain an overall better understanding of these concepts. I would highly encourage the viewers to check out one of my previous articles, where I have implemented the matrix multiplication from scratch without using any machine learning algorithms. You can do this from the link provided below. Performing such tasks will help you to gauge a better understanding of the various concepts and appreciate the quality of the libraries that we will study in the next step. 4. Dwelling Into The Various Libraries The best part about learning the Python programming language is the assistance of a variety of useful and fabulous libraries that this language offers us. The installations of most of these libraries are simple and efficient. They are productive and enables the Data Science enthusiasts to complete complex tasks within a few lines of code. (This can be noticed from the article that I had previously suggested.) Python offers a wide range of library modules and frameworks, making it one of the most compatible languages for constructing machine learning models and working on data science projects. The most commonly used python modules include numpy for numerical operations, scipy for scientific operations for dealing with something like sparse matrices, pandas to view the datasets in an organized manner, matplotlib and seaborn to visualize the data, analysis, and graphs of models constructed. You can also utilize the scikit-learn module in python for the development of machine learning models through the various algorithms options available in the sklearn library. Also, you construct deep learning models by making use of frameworks such as TensorFlow and Pytorch. The next mini-section involves a bonus section that will cover five of the more popular and useful data science libraries that a beginner must know about. Bonus: This Section will involve parts that I have discussed previously in my other articles. However, it is extremely beneficial for beginners, and would recommend giving it a read for the new viewers. If you already read this, feel free to skip ahead to the next step. In this part, we will discuss five of these significant library modules that are used in python for solving Data Science tasks. There are tons of frameworks available in python, but these five mentioned in this section of the article will cover the basic requirements to get started. 1. Pandas — The Pandas module is an open-source library in python to create data frames, which is extremely useful for organizing the data. Pandas is used extensively in the field of data science, machine learning, and deep learning for the structured arrangement of the data. The data frame created in pandas is a 2-dimensional representation of the data. After importing the Pandas library as pd, you can visualize the tabular data of your liking. An example of this is as shown below: Overall, the Pandas module is a fantastic library for systematic viewing of the data, and it also allows a wide variety of operations that can be performed. 2. Matplotlib — The Matplotlib module is one of the best tools for the visualization of the data frames or any other form of data. Matplotlib is used to visualize the data for exploratory data analysis in data science. It is extremely useful to understand the kind of data we are dealing with and to determine what is the next action that must be performed. The library offers an extensive variety of visualization functions such as scatter plot, bar plot, histograms, pie chart, and many other similar functions. Import matplotlib.pyplot module as plt for performing visualization tasks using matplotlib. An example of these can be seen below — Scatter Plot Bar Graph The scatter plots and bar graph plotted using matplotlib is shown in the figures. An advantage of the module is that it is very simple to use and efficient at providing visualizations. It can also be combined with the seaborn library for a more visual and aesthetic appeal. 3. NumPy — The NumPy library stands for Numerical Python. The numpy library is one of the best options for performing computations on matrix operations. It supports multi-dimensional arrays. An extensive amount of mathematical and logical operations can be performed on arrays. By converting lists into numpy arrays, we can perform computations like addition, subtraction, dot product, among many others. The use cases of numpy are applicable in both computer vision and natural language processing projects. In computer vision, you can use numpy arrays for visualizing the RGB or grayscale images in a numpy array and converting them accordingly. In natural language processing projects, you usually prefer to convert the text data into the form of vectors and numbers for optimized computation. Import numpy as np, and you can convert the text data into categorical data, as shown below: 4. Scikit-learn — The scikit-learn module is one of the best tools for machine learning and predictive data analysis. It offers a wide range of pre-built algorithms such as logistic regression, support vector machines (SVM’s), classification algorithms like K-means clustering, and a ton more operations. This is the best way for beginners to get started with machine learning algorithms because of the simple and efficient tools that this module grants access to. It is open-source and commercially usable while granting accessibility to almost anyone. It is reusable and supported by libraries such as NumPy, SciPy, and Matplotlib. import the sklearn module to run the scikit-learn code. Below is a code example for splitting the dataset we have into the form of train and test or validation data. This is useful for training and evaluation of the models. 5. NLTK — The NLTK library stands for the natural language toolkit platform, which is one of the best libraries for machine learning of natural language processing data. Natural Language Processing (NLP) is a branch of AI that helps computers to understand, interpret, and manipulate human language. The NLTK library is very well suited for linguistic-based tasks. It offers a wide range of options for tasks such as classification, tokenization, stemming, tagging, parsing, and semantic reasoning. It allows the user to chunk the data into entities that can be grouped together to produce a more organized meaning. The library can be imported as nltk, and below is an example code for the tokenization of a sentence.

https://towardsdatascience.com/12-steps-for-beginner-to-pro-in-data-science-in-12-months-c6f6ba01f96e

['Bharath K']

2020-12-25 21:18:27.081000+00:00

['Machine Learning', 'Success', 'Artificial Intelligence', 'Productivity', 'Data Science']

How the Pajama Conspiracy Saved the World

Pajamas. Is there anything more comforting? Anything more embracing? Anything more hot cocoa and afghan and fireplace? When you’re wearing soft, cotton, unitard pajamas, you don’t think of dark alleys or horror movies. You think tucked in, childhood, and every little thing’s gonna be all right. Something interesting has been happening on Facebook. Facebook is being overtaken by families and their pets wearing matching pajamas. Moms, dogs, dads, cats, mice, children, ferrets. It’s out of control. Every time I think I’ve seen the last family pajama photo, another one springs up, like a hydra. There was a time when I had quit Facebook because I was tired of feeling like everyone was having a wonderful life, while I was living a moderate one. But then COVID hit, and I was like “What’s up people?” Or I was, until now, when this pajama thing is making me feel left out again. I know that I just could buy a set for my family, but I don’t get it. Facebook friends and people Facebook adjacent, I’m telling you, there is something suspicious going on with all these pajamas. People laying in bed with their dogs in pajamas, lying fireside with their families in pajamas, couple snuggling up on a couch in pajamas. Honestly, I feel a little uncomfortable, like I’m a peeping Tom. When did it become acceptable to post yourself in your bedtime gear? My grandma would have been like, “Put on a robe. Cover your hair with a sleep bonnet.” She wouldn't have necessarily said, “That family looks slutty,” but she would have thought it. She had a Southern way of letting people know that they were drawing outside the lines. She would have said, looking at those people sprawled out in their pjs, “Doesn’t that just make you sad?” And craving her approval, I would have said, “Hell yeah it does.” What’s next, people? Everyone wearing matching nighties? A little Fredricks of Hollywood family photo for New Year's Eve? Gateway clothing, baby. Starts with a onesie ends with a nonesie. I, too, was targeted by the pajama cult, pre-holiday. I got lots of ads and pictures of families wearing the same pjs, and I considered, but I didn’t purchase. I did imagine my family and our dog all saddled up in matching onesies, but then my sphincter reaction jarred me back into reality. If they were selling big, old, faded t-shirts for the whole family, I’d click purchase. Because that’s real, man. Or jeans you’re too tired to take off for the whole family, click click click, but PJs with Christmas trees? Honey. We’re half Jewish. And honestly, if they were selling pajama sets with dreidel tops and Christmas tree bottoms, I still wouldn't have a bit. Why? Because I don’t want to dress up like my eleven-year-old son, fifty-year-old husband, and my thirty-five-year-old dog who chews on her nether regions? I don’t believe in QAnon and I definitely don’t believe Hillary Clinton eats babies, but there is something going on with these pajamas. Look at all their Manchurian candidate faces. Look how happy they all seem in their pajamas during a pandemic. I know that I’m missing something. But what is it? Maybe, I’m looking at it wrong. Maybe, 2020 led me to believe that every conspiracy is bad. What if that pajama joy real? What if those pajamas click a box that guarantees a creepy but legitimate smile for the whole family? It makes me wonder, with all this divisiveness in this country, all this hate and fear, do the pajamas help? Will pajamas be that tether, that pulls this country together? People of all colors and classes and genders embracing the onesie as onesie perfect union? And if so, sign me up. Purchase permitted. I will make that sacrifice. I will wear the same outfit as my dog, and I will say “Peace on earth, goodwill to Amazon.”

https://medium.com/the-haven/how-the-pajama-conspiracy-saved-the-world-f14ec2c54f95

['Amy Culberg']

2020-12-28 06:53:14.007000+00:00

['Self-awareness', 'Humor', 'Self', 'Self Help', 'Amazon']

Creating the Whole Machine Learning Pipeline with PyCaret

Creating the Whole Machine Learning Pipeline with PyCaret How to Create a Machine Learning Pipeline with PyCaret This tutorial covers the entire ML process, from data ingestion, pre-processing, model training, hyper-parameter fitting, predicting and storing the model for later use. We will complete all these steps in less than 10 commands that are naturally constructed and very intuitive to remember, such as create_model(), tune_model(), compare_models() plot_model() evaluate_model() predict_model() Let’s see the whole picture Image by Author Recreating the entire experiment without PyCaret requires more than 100 lines of code in most libraries. The library also allows you to do more advanced things, such as advanced pre-processing, ensembling, generalized stacking, and other techniques that allow you to fully customize the ML pipeline and are a must for any data scientist. PyCaret is an open source, low-level library for ML with Python that allows you to go from preparing your data to deploying your model in minutes. Allows scientists and data analysts to perform iterative data science experiments from start to finish efficiently and allows them to reach conclusions faster because much less time is spent on programming. This library is very similar to Caret de R, but implemented in python When working on a data science project, it usually takes a long time to understand the data (EDA and feature engineering). So, what if we could cut the time we spend on the modeling part of the project in half? Let’s see how First we need this pre-requisites Python 3.6 or later PyCaret 2.0 or later Here you can find the library docs and others. Also, you can follow this notebook with the code. First of all, please run this command: !pip3 install pycaret For Google Colab users: If you are running this notebook in Google Colab, run the following code at the top of your notebook to display interactive images from pycaret.utils import enable_colab enable_colab() Pycaret Modules Pycaret is divided according to the task we want to perform, and has different modules, which represent each type of learning (supervised or unsupervised). For this tutorial, we will be working on the supervised learning module with a binary classification algorithm. Classification Module The PyCaret classification module ( pycaret.classification ) is a supervised machine learning module used to classify elements into a binary group based on various techniques and algorithms. Some common uses of classification problems include predicting client default (yes or no), client abandonment (client will leave or stay), disease encountered (positive or negative) and so on. The PyCaret classification module can be used for binary or multi-class classification problems. It has more than 18 algorithms and 14 plots for analyzing model performance. Whether it’s hyper-parameter tuning, ensembling or advanced techniques such as stacking, PyCaret’s classification module has it all. Image by Author For this tutorial we will use an UCI data set called Default of Credit Card Clients Dataset. This data set contains information about default payments, demographics, credit data, payment history and billing statements of credit card customers in Taiwan from April 2005 to September 2005. There are 24,000 samples and 25 characteristics. The dataset can be found here. Or here you’ll find a direct link to download. So, download the dataset to your environment, and then we are going to load it like this In [2]: import pandas as pd In [3]: df = pd.read_csv('datasets/default of credit card clients.csv') In [4]: df.head() Out[4]: Image by Author 1- Get the data We also have another way to load it. In fact this will be the default way we will be working with in this tutorial. It is directly from the PyCaret datasets, and it is the first method of our Pipeline Image by Author from pycaret.datasets import get_data dataset = get_data('credit') #check the shape of data dataset.shape In order to demonstrate the predict_model() function on unseen data, a sample of 1200 records from the original dataset has been retained for use in the predictions. This should not be confused with a train/test split, since this particular split is made to simulate a real-life scenario. Another way of thinking about this is that these 1200 records are not available at the time the ML experiment was performed. In [7]: ## sample returns a random sample from an axis of the object. That would be 22,800 samples, not 24,000 data = dataset.sample(frac=0.95, random_state=786) In [8]: data Image by Author # we remove from the original dataset this random data data_unseen = dataset.drop(data.index) In [10]: data_unseen ## we reset the index of both datasets data.reset_index(inplace=True, drop=True) data_unseen.reset_index(inplace=True, drop=True) print('Data for Modeling: ' + str(data.shape)) print('Unseen Data For Predictions: ' + str(data_unseen.shape)) Data for Modeling: (22800, 24) Unseen Data For Predictions: (1200, 24) Split data The way we divide our data set is important because there is data that we'll not use during the modeling process, and we'll use at the end to validate our results by simulating real data. The data we use for modeling we sub-divide it in order to evaluate two scenarios, training and testing. Therefore, the following has been done Image by Author Unseen data set (also known as validation data set) Is the data sample used to provide an unbiased assessment of a final model. The validation data set provides the gold standard used to evaluate the model. It is only used once the model is fully trained (using the training and test sets). The validation set is generally what is used to evaluate the models of a competition (for example, in many Kaggle or DataSource.ai competitions, the test set is initially released along with the training and test set and the validation set is only released when the competition is about to close, and it is the result of the validation set model that decides the winner). Many times the test set is used as the validation set, but it is not a good practice. The validation set is generally well healed. It contains carefully sampled data covering the various classes that the model would face, when used in the real world. Training data set Training data set: The data sample used to train the model. The data set we use to train the model The model sees and learns from this data. Test data set Test Data Set: The data sample used to provide an unbiased assessment of a model is matched to the training data set while adjusting the model’s hyperparameters. The assessment becomes more biased as the skill in the test data set is incorporated into the model configuration. The test set is used to evaluate a given model, but this is for frequent evaluation. We, as ML engineers, use this data to fine-tune the hyperparameters of the model. Therefore, the model occasionally sees this data, but never “learns” from it. We use the results of the test set, and update the higher level hyperparameters So the test set impacts a model, but only indirectly. The test set is also known as the Development set. This makes sense, since this dataset helps during the “development” stage of the model. Confusion of terms There is a tendency to mix up the name of test and validation. Depending on the tutorial, the source, the book, the video or the teacher/mentor the terms are changed, the important thing is to keep the concept. In our case we already separated the validation set at the beginning (1,200 samples of data_unseen ) 2- Setting up the PyCaret environment Image by Author Now let’s set up the Pycaret environment. The setup() function initializes the environment in pycaret and creates the transformation pipeline to prepare the data for modeling and deployment. setup() must be called before executing any other function in pycaret. It takes two mandatory parameters: a pandas dataframe and the name of the target column. Most of this part of the configuration is done automatically, but some parameters can be set manually. For example: The default division ratio is 70:30 (as we see in above paragraph), but can be changed with " train_size ". (as we see in above paragraph), but can be changed with " ". K-fold cross-validation is set to 10 by default by default “session_id " is our classic " random_state " In [12]: ## setting up the environment from pycaret.classification import * Note: After you run the following command you must press enter to finish the process. We will explain how they do it. The setup process may take some time to complete. In [13]: model_setup = setup(data=data, target='default', session_id=123) Image by Author When you run setup() , PyCaret's inference algorithm will automatically deduce the data types of all features based on certain properties. The data type must be inferred correctly but this is not always the case. To take this into account, PyCaret displays a table containing the features and their inferred data types after setup() is executed. If all data types are correctly identified, you can press enter to continue or exit to end the experiment. We press enter, and should come out the same output as we got above. Ensuring that the data types are correct is critical in PyCaret, as it automatically performs some pre-processing tasks that are essential to any ML experiment. These tasks are performed differently for each type of data, which means that it is very important that they are correctly configured. We could overwrite the type of data inferred from PyCaret using the numeric_features and categorical_features parameters in setup() . Once the setup has been successfully executed, the information grid containing several important pieces of information is printed. Most of the information is related to the pre-processing pipeline that is built when you run setup() Most of these features are out of scope for the purposes of this tutorial, however, some important things to keep in mind at this stage include session_id : A pseduo-random number distributed as a seed in all functions for later reproducibility. : A pseduo-random number distributed as a seed in all functions for later reproducibility. Target type : Binary or Multiclass. The target type is automatically detected and displayed. Label encoded: When the Target variable is of type string (i.e. ‘Yes’ or ‘No’) instead of 1 or 0, it automatically codes the label at 1 and 0 and shows the mapping (0 : No, 1 : Yes) as reference as reference Original data : Displays the original form of the data set. In this experiment (22800, 24) ==> Remember: "Seeing data" ==> Remember: "Seeing data" Missing values : When there are missing values in the original data this will be shown as True Numerical features : The number of features inferred as numerical. Categorical features : The number of features inferred as categorical Transformed train sets: Note that the original form of (22800, 24) is transformed into (15959, 91) for the transformed train set and the number of features has increased from 24 to 91 due to the categorical coding is transformed into for the transformed train set and Transformed test set: There are 6,841 samples in the test set. This split is based on the default value of 70/30 which can be changed using the train_size parameter in the configuration. Note how some tasks that are imperative to perform the modeling are handled automatically, such as imputation of missing values (in this case there are no missing values in the training data, but we still need imputers for the unseen data), categorical encoding, etc. Most of the setup() parameters are optional and are used to customize the preprocessing pipeline. 3- Compare Models Image by Author In order to understand how PyCaret compares the models and the next steps in the pipeline, it is necessary to understand the concept of N-Fold Coss-Validation. N-Fold Coss-Validation Calculating how much of your data should be divided into your test set is a delicate question. If your training set is too small, your algorithm may not have enough data to learn effectively. On the other hand, if your test set is too small, then your accuracy, precision, recall and F1 score could have a large variation. You may be very lucky or very unlucky! In general, putting 70% of your data in the training set and 30% of your data in the test set is a good starting point. Sometimes your data set is so small that dividing it 70/30 will result in a large amount of variance. One solution to this is to perform N-Fold cross-validation. The central idea here is that we are going to do this whole process N times and then average the accuracy. For example, in a 10 times cross validation, we will make the test set the first 10% of the data and calculate the accuracy, precision, recall and F1 score. Then, we will make the cross-validation establish the second 10% of the data and we will calculate these statistics again. We can do this process 10 times, and each time the test set will be a different piece of data. Then we average all the accuracies, and we will have a better idea of how our model works on average. Note: Validation Set (yellow here) is the Test Set in our case Image by Author Understanding the accuracy of your model is invaluable because you can start adjusting the parameters of your model to increase its performance. For example, in the K-Nearest Neighbors algorithm, you can see what happens to the accuracy as you increase or decrease K . Once you are satisfied with the performance of your model, it's time to enter the validation set. This is the part of your data that you split at the beginning of his experiment ( unseen_data in our case). It is supposed to be a substitute for the real-world data that you are really interested in sorting out. It works very similar to the test set, except that you never touched this data while building or refining your model. By finding the precision metrics, you get a good understanding of how well your algorithm will perform in the real world. Comparing all models Comparing all models to evaluate performance is the recommended starting point for modeling once the PyCaret setup() is completed (unless you know exactly what type of model is needed, which is often not the case), this function trains all models in the model library and scores them using a stratified cross-validation for the evaluation of the metrics. The output prints a score grid that shows the average of the Accuracy, AUC, Recall, Precision, F1, Kappa, and MCC across the folds ( 10 by default) along with the training times. Let's do it! In [14]: best_model = compare_models() Image by Author The compare_models() function allows you to compare many models at once. This is one of the great advantages of using PyCaret. In one line, you have a comparison table between many models. Two simple words of code (not even one line) have trained and evaluated more than 15 models using the N-Fold cross-validation. The above printed table highlights the highest performance metrics for comparison purposes only. The default table is sorted using “Accuracy” (highest to lowest) which can be changed by passing a parameter. For example, compare_models(sort = 'Recall') will sort the grid by Recall instead of Accuracy. If you want to change the Fold parameter from the default value of 10 to a different value, you can use the fold parameter. For example compare_models(fold = 5) will compare all models in a 5-fold cross-validation. Reducing the number of folds will improve the training time. By default, compare_models returns the best performing model based on the default sort order, but it can be used to return a list of the top N models using the n_select parameter. In addition, it returns some metrics such as accuracy, AUC and F1. Another cool thing is how the library automatically highlights the best results. Once you choose your model, you can create it and then refine it. Let's go with other methods. In [15]: print(best_model) RidgeClassifier(alpha=1.0, class_weight=None, copy_X=True, fit_intercept=True, max_iter=None, normalize=False, random_state=123, solver='auto', tol=0.001) 4- Create the Model Image by Author create_model is the most granular function in PyCaret and is often the basis for most of PyCaret's functionality. As its name indicates, this function trains and evaluates a model using a cross-validation that can be set with the parameter fold . The output prints a scoring table showing by Fold the Precision, AUC, Recall, F1, Kappa and MCC. For the rest of this tutorial, we will work with the following models as our candidate models. The selections are for illustrative purposes only and do not necessarily mean that they are the best performers or ideal for this type of data Decision Tree Classifier (‘dt’) K Neighbors Classifier (‘knn’) Random Forest Classifier (‘rf’) There are 18 classifiers available in the PyCaret model library. To see a list of all classifiers, check the documentation or use the models() function to view the library. In [16]: models() Image by Author dt = create_model('dt') Image by Author #trained model object is stored in the variable 'dt'. print(dt) DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini', max_depth=None, max_features=None, max_leaf_nodes=None, min_impurity_decrease=0.0, min_impurity_split=None, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, presort='deprecated', random_state=123, splitter='best') In [19]: knn = create_model('knn') Image by Author print(knn) KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski', metric_params=None, n_jobs=-1, n_neighbors=5, p=2, weights='uniform') In [21]: rf = create_model('rf') Image by Author print(rf) RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None, criterion='gini', max_depth=None, max_features='auto', max_leaf_nodes=None, max_samples=None, min_impurity_decrease=0.0, min_impurity_split=None, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, n_estimators=100, n_jobs=-1, oob_score=False, random_state=123, verbose=0, warm_start=False) Note that the average score of all models matches the score printed on compare_models() . This is because the metrics printed in the compare_models() score grid are the average scores of all the folds. You can also see in each print() of each model the hyperparameters with which they were built. This is very important because it is the basis for improving them. You can see the parameters for RandomForestClassifier max_depth=None max_features='auto' min_samples_leaf=1 min_samples_split=2 min_weight_fraction_leaf=0.0 n_estimators=100 n_jobs=-1 5- Tunning the Model Image by Author When creating a model using the create_model() function the default hyperparameters are used to train the model. To tune the hyperparameters the tune_model() function is used. This function automatically tunes the hyperparameters of a model using the Random Grid Search in a predefined search space. The output prints a score grid showing the accuracy, AUC, Recall, Precision, F1, Kappa and MCC by Fold for the best model. To use a custom search grid, you can pass the custom_grid parameter in the tune_model function In [23]: tuned_rf = tune_model(rf) Image by Author If we compare the Accuracy metrics of this refined RandomForestClassifier model with the previous RandomForestClassifier, we see a difference, because it went from an Accuracy of 0.8199 to an Accuracy of 0.8203 . In [24]: #tuned model object is stored in the variable 'tuned_dt'. print(tuned_rf) RandomForestClassifier(bootstrap=False, ccp_alpha=0.0, class_weight={}, criterion='entropy', max_depth=5, max_features=1.0, max_leaf_nodes=None, max_samples=None, min_impurity_decrease=0.0002, min_impurity_split=None, min_samples_leaf=5, min_samples_split=10, min_weight_fraction_leaf=0.0, n_estimators=150, n_jobs=-1, oob_score=False, random_state=123, verbose=0, warm_start=False) Let’s compare now the hyperparameters. We had these before. max_depth=None max_features='auto' min_samples_leaf=1 min_samples_split=2 min_weight_fraction_leaf=0.0 n_estimators=100 n_jobs=-1 Now these: max_depth=5 max_features=1.0 min_samples_leaf=5 min_samples_split=10 min_weight_fraction_leaf=0.0 n_estimators=150 n_jobs=-1 You can make this same comparisson with knn and dt by yourself and explore the differences in the hyperparameters. By default, tune_model optimizes Accuracy but this can be changed using the optimize parameter. For example: tune_model(dt, optimize = 'AUC') will look for the hyperparameters of a Decision Tree Classifier that results in the highest AUC instead of Accuracy. For the purposes of this example, we have used Accuracy's default metric only for simplicity. Generally, when the data set is unbalanced (like the credit data set we are working with) Accuracy is not a good metric to consider. The methodology underlying the selection of the correct metric to evaluate a rating is beyond the scope of this tutorial. Metrics alone are not the only criteria you should consider when selecting the best model for production. Other factors to consider include training time, standard deviation of k-folds, etc. For now, let’s go ahead and consider the Random Forest Classifier tuned_rf , as our best model for the rest of this tutorial 6- Plotting the Model Image by Author Before finalizing the model (Step # 8), the plot_model() function can be used to analyze the performance through different aspects such as AUC, confusion_matrix, decision boundary etc. This function takes a trained model object and returns a graph based on the training/test set. There are 15 different plots available, please refer to plot_model() documentation for a list of available plots. In [25]: ## AUC Plot plot_model(tuned_rf, plot = 'auc') Image by Author ## Precision-recall curve plot_model(tuned_rf, plot = 'pr') Image by Author ## feature importance plot_model(tuned_rf, plot='feature') Image by Author ## Consufion matrix plot_model(tuned_rf, plot = 'confusion_matrix') Image by Author 7- Evaluating the model Image by Author Another way to analyze model performance is to use the evaluate_model() function which displays a user interface for all available graphics for a given model. Internally it uses the plot_model() function. In [29]: evaluate_model(tuned_rf) 8- Finalizing the Model Image by Author The completion of the model is the last step of the experiment. A normal machine learning workflow in PyCaret starts with setup() , followed by comparison of all models using compare_models() and pre-selection of some candidate models (based on the metric of interest) to perform various modeling techniques, such as hyperparameter fitting, assembly, stacking, etc. This workflow will eventually lead you to the best model to use for making predictions on new and unseen data. The finalize_model() function fits the model to the complete data set, including the test sample (30% in this case). The purpose of this function is to train the model on the complete data set before it is deployed into production. We can execute this method after or before the predict_model() . We're going to execute it after of it. One last word of caution. Once the model is finalized using finalize_model() , the entire data set, including the test set, is used for training. Therefore, if the model is used to make predictions about the test set after finalize_model() is used, the printed information grid will be misleading since it is trying to make predictions about the same data that was used for the modeling. To demonstrate this point, we will use final_rf in predict_model() to compare the information grid with the previous. In [30]: final_rf = finalize_model(tuned_rf) In [31]: #Final Random Forest model parameters for deployment print(final_rf) RandomForestClassifier(bootstrap=False, ccp_alpha=0.0, class_weight={}, criterion='entropy', max_depth=5, max_features=1.0, max_leaf_nodes=None, max_samples=None, min_impurity_decrease=0.0002, min_impurity_split=None, min_samples_leaf=5, min_samples_split=10, min_weight_fraction_leaf=0.0, n_estimators=150, n_jobs=-1, oob_score=False, random_state=123, verbose=0, warm_start=False) 9- Predicting with the model Image by Author Before finalizing the model, it is advisable to perform a final check by predicting the test/hold-out set ( data_unseen in our case) and reviewing the evaluation metrics. If you look at the information table, you will see that 30% (6,841 samples) of the data have been separated as training/set samples. All of the evaluation metrics we have seen above are cross-validated results based on the training set (70%) only. Now, using our final training model stored in the tuned_rf variable we predict against the test sample and evaluate the metrics to see if they are materially different from the CV results In [32]: predict_model(final_rf) Image by Author The accuracy of the test set is 0.8199 compared to the 0.8203 achieved in the results of the tuned_rf . This is not a significant difference. If there is a large variation between the results of the test set and the training set, this would normally indicate an over-fitting, but it could also be due to several other factors and would require further investigation. In this case, we will proceed with the completion of the model and the prediction on unseen data (the 5% that we had separated at the beginning and that was never exposed to PyCaret). (TIP: It is always good to look at the standard deviation of the results of the training set when using create_model() . The predict_model() function is also used to predict about the unseen data set. The only difference is that this time we will pass the parameter data_unseen . data_unseen is the variable created at the beginning of the tutorial and contains 5% (1200 samples) of the original data set that was never exposed to PyCaret. In [33]: unseen_predictions = predict_model(final_rf, data=data_unseen) unseen_predictions.head() Image by Author Please go to the last column of this previous result, and you will see a new feature called Score Image by Author Label is the prediction and score is the probability of the prediction. Note that the predicted results are concatenated with the original data set, while all transformations are automatically performed in the background. We have finished the experiment finalizing the tuned_rf model that now is stored in the final_rf variable. We have also used the model stored in final_rf to predict data_unseen . This brings us to the end of our experiment, but one question remains: What happens when you have more new data to predict? Do you have to go through the whole experiment again? The answer is no, PyCaret's built-in save_model() function allows you to save the model along with all the transformation pipe for later use and is stored in a Pickle in the local environment (TIP: It’s always good to use the date in the file name when saving models, it’s good for version control) Let’s see it in the next step 10- Save/Load Model for Production Image by Author Save Model In [35]: save_model(final_rf, 'datasets/Final RF Model 19Nov2020') Transformation Pipeline and Model Succesfully Saved Out[35]: (Pipeline(memory=None, steps=[('dtypes', DataTypes_Auto_infer(categorical_features=[], display_types=True, features_todrop=[], id_columns=[], ml_usecase='classification', numerical_features=[], target='default', time_features=[])), ('imputer', Simple_Imputer(categorical_strategy='not_available', fill_value_categorical=None, fill_value_numerical=None, numeric_stra... RandomForestClassifier(bootstrap=False, ccp_alpha=0.0, class_weight={}, criterion='entropy', max_depth=5, max_features=1.0, max_leaf_nodes=None, max_samples=None, min_impurity_decrease=0.0002, min_impurity_split=None, min_samples_leaf=5, min_samples_split=10, min_weight_fraction_leaf=0.0, n_estimators=150, n_jobs=-1, oob_score=False, random_state=123, verbose=0, warm_start=False)]], verbose=False), 'datasets/Final RF Model 19Nov2020.pkl') Load Model To load a model saved at a future date in the same or an alternative environment, we would use PyCaret’s load_model() function and then easily apply the saved model to new unseen data for the prediction In [37]: saved_final_rf = load_model('datasets/Final RF Model 19Nov2020') Transformation Pipeline and Model Successfully Loaded Once the model is loaded into the environment, it can simply be used to predict any new data using the same predict_model() function. Next we have applied the loaded model to predict the same data_unseen we used before. In [38]: new_prediction = predict_model(saved_final_rf, data=data_unseen) In [39]: new_prediction.head() Out[39]: Image by Author from pycaret.utils import check_metric check_metric(new_prediction.default, new_prediction.Label, 'Accuracy') Out[41]: 0.8167 Pros & Cons As with any new library, there is still room for improvement. We'll list some of the pros and cons we found while using the library. Pros: It makes the modeling part of your project much easier. You can create many different analyses with just one line of code. Forget about passing a list of parameters when fitting the model. PyCaret does it automatically for you. You have many different options to evaluate the model, again, with just one line of code Since it is built on top of famous ML libraries, you can easily compare it with your traditional method Cons: The library is in its early versions, so it is not mature enough and is susceptible to bugs. Not big deal to be honest As all Auto ML libraries, it's a black box, so you can't really see what's going on inside it. Therefore, I would not recommend it for beginners. It might make the learning process a bit superficial. Conclusions This tutorial has covered the entire ML process, from data ingestion, pre-processing, model training, hyper-parameter fitting, predicting and storing the model for later use. We have completed all these steps in less than 10 commands that are naturally constructed and very intuitive to remember, such as create_model(), tune_model(), compare_models() . Recreating the whole experiment without PyCaret would have required more than 100 lines of code in most of the libraries. The library also allows you to do more advanced things, such as advanced pre-processing, assembly, generalized stacking, and other techniques that allow you to fully customize the ML pipeline and are a must for any data scientist I hope you enjoyed this reading! you can follow me on twitter or linkedin

https://towardsdatascience.com/creating-the-whole-machine-learning-pipeline-with-pycaret-db39a3006840

['Daniel Morales']

2020-12-06 19:22:03.300000+00:00

['Machine Learning', 'Python', 'Data Science', 'Artificial Intelligence']

What You Should Know About Criticism

When Constructive Criticism Gets Out of Hand We are all often critical sometimes, and it’s not necessarily a bad thing. We understand that our colleague, spouse, boss, or coach has our best interest at heart. To criticize constructively means you’re thinking carefully. It is a skill that helps us navigate the world and our relationships in an objective way. It helps us sharpen our skills and increases our chances of accelerated progress. Constructive criticism is about making the world better but when you're being too critical of others you're making yourself feel better. And this is where the opposite of objectivity sets in. Being too critical of others can make us narrow-minded and blind, especially to ourselves. One of the reasons to easily slip into habitually criticizing others is that it makes us feel good without even knowing it. When constructive criticism gets out of hand, it becomes hateful criticism.

https://medium.com/be-unique/what-you-should-know-about-criticism-bc67294cc686

['Emeka Nwanedo']

2020-06-29 01:35:13.945000+00:00

['Personal Development', 'Work', 'Productivity', 'Entrepreneurship', 'Life']

From Self-Diagnosis to Self-Realization

These children are a subset of a subset of a subset of a subset of the actual Autistic population. And yet they made up the entire foundation on which all research and all diagnostic tools for Autistic people are based. From the 1940’s until about the mid-1990’s, nearly all Autism specialists based their treatment and diagnosis on an understanding of Autism that excluded adults, women, people of color, transgender people, poor people, and people who had learned to hide their Autistic traits. To this day, many assessors are ill-equipped to deal with any of these populations. People are still regularly dismissed from being assessed because they do not meet the stereotypes of what an Autistic person “looks like”. Some clinicians still refuse to diagnose Autism in women and girls, or they’ll disregard a person’s suspected Autism because they seem too “polite” or “normal”. Clinicians are not consistent with one another in how they assess Autism, which tools they use and how they go about using them. And no matter how talented or sensitive the clinician is, they are still performing adult assessments using instruments that were developed for children. The CDC website still completely ignores the topic of diagnosing Autism in adults. When I was a child, I had many of the most stereotypical markers of Autism, from poor motor coordination, to social and sensory issues, to using a large vocabulary at an atypically young age. I was the picture of what back then would have been called Asperger's. I was given a ton of assessments for other issues, such as my motor problems, but not for Autism itself. The most likely reason for this is that society saw me as a “girl”, and everyone knew back then that girls don’t get Autism. I know countless Autistic adults (formally diagnosed and self-diagnosed) who similarly slipped through the cracks. The tests that are used to categorize us are as far from objective and rational as they could possibly be. Even when a test is administered well, it basically comes down to asking a person to honestly reflect on whether or not they have any Autistic traits. An adult human is absolutely capable of doing that on their own. Often, we know ourselves vastly better than clinicians do. We have a larger pool of data on ourselves than they will ever have. … I also oppose formal diagnosis because Autism is not a simple category that you either belong to or don’t belong to. No one can actually determine whether a person “has Autism” in a binary sense, the way we can screen for a tumor or strep throat. Autism exists in a series of spectrums, and they all vary a great deal from person to person. A spectrum of colors. Photo by Kirill Sharkovski on Unsplash One Autistic person might be extremely sensitive to sound, so much so that being on a crowded bus makes them want to vomit. Another Autistic person might not be bothered by sound much, but might find wearing tight clothing to be absolute torture. Some Autistic people do a lot of obvious self-stimulatory behavior — they rock in place, click their tongues, or flap their hands all day long. Some keep it very subtle. Some Autistic people can’t make eye contact; others can. We’re all unique beautiful angels; in fact, our brains are organized in more diverse and unique ways than neurotypical people’s brains are. What this means is that a person could be right near the edge of the diagnostic cut-off, on every single Autistic trait, but still not count as Autistic in a professional’s eyes. Clearly this would be someone who has tons of experiences in common with Autistic people. They might struggle with bright lights or strange food textures. They might take jokes very literally, or not be able to detect sarcasm. They might have melt-downs the way many of us do. And they probably would benefit from the same kinds of resources that officially “Autistic” people benefit from. But because of where the line was drawn in the sand by professionals, those people are not really Autistic. To me, that’s not only irrational and lacking in scientific precision — it’s fundamentally unjust. I believe our community has a lot to gain by letting sub-clinical Autism-spectrum people under the Autistic umbrella with us. We share common interests and experiences. We deal with similar difficulties as we move through the world. There is strength in numbers, and the more people we have advocating for sensory-friendly spaces and lax social rules, the more Autistic people will stand to benefit. Why gatekeep who is deserving of community and help? A variety of brightly-colored umbrellas, hanging on strings forming a canopy. Photo by Ricardo Resende on Unsplash … Everything useful that I’ve learned about Autism, I have learned from Autistic people. Fellow Autistics taught me how to limit my sensory input and ground myself when I’m feeling stressed. They gave me permission to reduce my social contact, and to stop presenting myself as the bubbly, outgoing feminine person society had pressured me to be. Autistic people introduced me to weighted blankets and fidget jewelry and sensory slime; they helped me discover when I was at risk of experiencing melt-downs. Most importantly, they helped to normalize every difficult and alienated feeling I have ever had. You know what Autism experts have done for me? Nothing. Clinicians generally see Autism as a disorder to be treated, or a malady to be “cured”. Yet they offer no treatments for adults that make Autistic traits any less severe or intense. That’s because there are no such treatments. Autism cannot be cured or removed from a person who has it. It is a fundamental component of who we are. Autism is a type of functioning and a way of being. Just as a Deaf person often cannot be “cured” of their Deafness, but must instead be accommodated by hearing society, Autistic people cannot be “cured”. We need and deserve societal acceptance instead. This is at the heart, really, of why I oppose a medicalized framework to Autism and defining who is Autistic. Autistic people are not broken or sick. Autism is not something to be measured, quantified, prescribed a treatment for, and cured. Many of us would never want to be cured even if a cure existed — because Autism is a fundamental part of who we are. And there are many benefits and joys that come with being Autistic. Unfortunately, the clinical and legal power structures do not see Autism this way. And in many cases, getting diagnosed with Autism can bring a great deal of difficulty and ostracism to a person’s life. For years, Canada would not let a person immigrate to the country if they were Autistic. Autistic transgender people, like me, are often denied access to necessary medical care and gender-affirming treatment. We aren’t trusted to define our own genders, because Autism is seen as causing impaired judgement. And generally, if a medical provider sees an Autism diagnosis in your records, they will treat you with condescension and disrespect at best. At worst, you may lose your legal autonomy. As you can see, there is very little to gain from getting a formal, medicalized Autism diagnosis, and a significant amount to lose. So where do we go from here? If Autism is not a diagnostic category, what is it? … A row of people, backlit by the sun. Photo by Kevin Delvecchio on Unsplash I would like to propose a framework of Autism that is completely non-medicalized. Therapists, doctors, neuroscientists had 75 years to come to a firm and useful understanding of Autism, and they blew it. They called us less than human. They conspired with Nazis to have us eradicated. They erased those of us who weren’t white cis boys who loved trains. They tried to cure us and created more stigma for us. They advocated to have our kind completely erased from existence. They ignored us when we asked for help managing the social and sensory traumas of existing in an allistic world. They don’t get to define who we are and what we need anymore. They botched it irreparably. Now it is time that Autistic people take our fates into our own hands. I am pro self-realization of Autism. I am pro self-identification as Autistic. I believe that if you speak to Autistic people, learn about what our lives are like, come to understand our challenges, and find that you identify with us, then that is enough. I don’t care if you would be categorized as Autistic by some outmoded diagnostic tool created for children and later adapted, poorly, to flag a handful of the most stereotypical Autistic adults. I don’t care if you spent thousands of dollars trying to get a doctor to validate what years of self-knowledge has taught you. I truly don’t care what the doctors think. I want to hear what you think. And I don’t think you need to be cured. You don’t need to lessen your obvious signs of Autism, to be accommodating and palatable to a society that has been unfair to you all your life. I believe you deserve community and acceptance. I believe it is the world that must learn how to accommodate you. Under this framework, it is neurotypical society that must change and seek treatment, not Autistic people. The only way for Autistic people to thrive is for us to oppose any system of power that says we are something to be measured, monitored, contained, and controlled. And in order for society to function, neurotypicals must learn to get used to us, because we are growing in numbers, and not going away. There are far, far more of us than any researcher or diagnostician has been able to accurately estimate, because their tools are so shoddy. They cannot erase us from existence, because we are not a disease to be purged. And I hope that lack of understanding and control makes neurotypical Autism “experts” absolutely quake with anxiety. We can’t be contained if we don’t let them contain us. The time for submitting to their systems has ended. I believe in Autistic autonomy. I believe in our agency and self-knowledge. I don’t believe in diagnosis.

https://devonprice.medium.com/from-self-diagnosis-to-self-realization-852e3a069451

['Devon Price']

2019-08-14 21:41:17.851000+00:00

['Equality', 'Mental Health', 'Psychology', 'Disability', 'Autism']

Why Am I So Nervous to Talk to People?

A friend recently asked me for some tips to help with her anxiety. She shared she was having a hard time preparing herself to go the store or to see friends in small gatherings. “It’s like I’ve forgotten how to act. I’m worried I’m going to do or say something stupid or awkward.” My friend isn’t the first one to mention this fear. Clients and other loved ones have (sometimes jokingly, sometimes seriously) mentioned their concern about having developed a social ineptitude. They are worried all the time that isolation has had a negative impact on their ability to socialize with ease. For those with preexisting social anxiety, the pandemic may have had some silver linings. Suddenly it’s become the social norm to stay away from others. Cocooning in one’s home was seen as helpful as opposed to avoidant. However, as this 2020 article from the National Social Anxiety Center points out, the pandemic has caused a lot of treatment setbacks; in vivo exposure, or instruction to engage in social situations that make us uncomfortable, has obviously been put on hold in many ways (Rosen, 2020). Even if you’ve never previously struggled with social anxiety, it’s completely understandable if there’s an uptick in nerves when thinking about going to meet or speak in front of other people. The hallmark of social anxiety is a fear of being judged, critiqued or otherwise negatively evaluated by others. This can result in a feeling of self-consciousness in social situations or a general fear of meeting others (NIMH). These feelings might be heightened after a period of not being exposed to these situations. There are steps you can take to cope with and unlearn the thoughts and feelings associated with social anxiety. Try these tips below for easing yourself back into social situations.

https://medium.com/mind-cafe/why-am-i-so-nervous-to-talk-to-people-f5b240a5ad0f

['Kara Lissy']

2020-11-02 17:34:41.072000+00:00

['Personal Development', 'Life Lessons', 'Self', 'Mental Health', 'Psychology']

Spiritual Secrets Submission Guidelines (Updated 18/10/2020)

Why do I want to connect with Spiritual Secrets? Spirituality is an inevitable knowledge for today’s mankind to overcome the herculean mammoth like problems arising in their day to day lives. Spirituality can be used to conquer fear, putting down the burden of past relationships or events, achieve success, attain mental peace and stability, and even become free from the past guilt. Hence, spirituality can be used in all prospects to make our lives peaceful, happy, blissful, powerful, and valuable. Spirituality can open the doors of experiencing the innate powers of the soul: Peace, Happiness, Bliss, Power, Knowledge, Purity, and Love. And we strive here to share the stories that empower the soul. If you, too, want this world to transform into a paradise, let’s join hands!

https://medium.com/spiritual-secrets/spiritual-secrets-submission-guidelines-9b4b5d9a4384

['Darshak Rana']

2020-12-01 16:43:01.441000+00:00

['Storytelling', 'Writing', 'Universe', 'Spirituality', 'Mindfulness']

Do This on the Days You Hate Your Writing

Do This on the Days You Hate Your Writing This sentiment is a good sign One of the greatest writers ever, Franz Kafka, burned over 90 percent of his work. Some days I look at my writing and feel like pulling a Kafka. I want to throw it all out. It all looks like complete garbage to me. Perhaps a lot of it is. Many writers say they look back on their first few years of writing and cringe. I’m still in my first few years and luckily I cringe some days. Luckily? Yes. Cringing is a sign that my writing is improving. Here are a few ways I’ve found to turn the occasional negativity I have for my own work into improvement as a writer.

https://medium.com/illumination/what-to-do-on-the-days-you-hate-your-own-writing-a1e5f858ccdd

['Max Klein']

2020-08-06 17:22:10.741000+00:00

['Motivation', 'Writing', 'Reading', 'Persistence', 'Writing Tips']

Are the People You Hang Out With Good for You?

There are five qualities that healthy relationships all have. Respect You both respect and trust each other. You have similar values and ethics and know that you can count on one another to be there when it is important. Betrayal is not an option. You know that would never occur. Open communication If there is a problem in the relationship, you talk about it. There is no “silent treatment.” You feel comfortable addressing concerns with one another and don’t have to guess what the other person is thinking and feeling. Vulnerability Your trust allows you to share your fears and desires. You know that secrets will be kept in the utmost confidence. These friends are on your shortlist. You tell them things that you wouldn’t share with just anyone. Healthy boundaries Because you communicate well, you have established healthy boundaries. You feel comfortable telling one another if you need time to yourself. You don’t have to guess what is acceptable and what is overwhelming. You feel perfectly comfortable saying, “I’m sorry, but I can’t handle that right now. Can we talk later?” And the other person understands and respects that. There is a mutual give and take. Forgiveness If you have a misunderstanding or hurt one another, you can work through it and forgive one another. There is no punishment phase. You understand that each of you is 100% responsible for 50% of the relationship. Our inner circle of friends is important. Choose them wisely.

https://medium.com/artistic-mystic-soul/are-the-people-you-hang-out-with-good-for-you-17c5f8ef615b

['Lisa Beth Wright']

2020-12-20 23:53:05.086000+00:00

['Self-awareness', 'Relationships', 'Mental Health', 'Friendship', 'Life']

“Simplicity is the glory of expression” — Interview with Jalaj Thanaki

VK: If you were to write a book what would be the title of the book? What would be the main topics you would cover in the book? (Jalaj is the author of two books) — I will be doing a book review for the book on Acing AI so stay tuned and subscribe to our newsletter to not miss it. JT: Fortunately, I got the chance to write two books on topics which I wanted to write after my graduation. First one is “Python Natural Language Processing” which helps beginners to learn NLP from scratch and second one is “Machine Learning Solutions” which is practical guide that helps readers to build and optimize various Machine Learning applications. It includes applications from Natural Language Processing(NLP), computer vision and Reinforcement Learning domains. Given a chance I want to write a book entitled “Reusable Architecture for ML Applications”. Nowadays companies are having various types of projects and some of the project features are overlapped with other project features. How we can build the reusable architecture which helps developers to build the common project features easily across the multiple products. If the reusable architecture would be achieved then it would save a lot of development time and energy of Data Scientists and it would be efficient solutions for many companies. VK: In terms of time, money or energy what are the best investments you have made which have given you compounded rewards in your career? JT: After completion of my undergrad study, I had to choose between job and graduate study. I’m glad that I had chosen graduate study because as part of my thesis work I came to know about the NLP domain. That thesis work was my starting point in the Data Science field. I believe that “Simplicity is the glory of expression”. I always tried to make content as easy as possible for my readers so that they can understand complex data science related concepts really well. I prefer to write in simple language. As a result, my first book “Python Natural Language Processing” was considered as textbook by Weill Cornell Medicine, Department of Healthcare Policy & Research for their Natural Language Processing in Health course. I got to know lot about marketing, pre-sales, post-sales and so on after publishing my first book. Networking with students, researcher, industry experts and entrepreneurs is always delightful experience. People are ready to share their ideas and knowledge with others. I really enjoy that positive spirit. VK: What are some absurd ideas around data science experiments/projects that are not intuitive to people looking from outside in? JT: People who are unfamiliar to the data science field they think that machines can learn or think by themselves and the job of the Data Scientists/Machine Learning Engineers is just to monitor the process. VK: In the last year, what has improved your work life which could benefit others? JT: Since last year, apart for begin Data Scientist, I was writing my books. In order to manage these two projects, I had to have good time management skill. Initially it was really challenging for me but eventually I learnt how to manage my time efficiently. In order to do so, I used to prepare my weekly as well as daily to-do list so that I could know how much time I need to spend on each of the tasks. I usually try to make realistic plan which I can follow and I always have a room for watching YouTube videos.☺ Nowadays, I have cut out my time on unnecessary meetings and communications. I don’t spend too much time on social media (but I always resolve the questions coming from my followers.) All these steps help me to become more productive. VK: What advice would you give to someone starting in this field? What advice should they ignore? JT: I have number of things that I wanted to share with newbies and job seekers. There are many subdomains in data science. Such as analytics, NLP, computer vision, speech and so on. Please don’t pursue any subdomains of the data science just because others are pursuing it. Take your time. Try to understand your interest area. Getting confuse during this process is normal. Unlock yourself. Don’t be afraid of failing in your experiments. Try to clear your vision and to do so, first of all you need to read a lot as well as start implementing number of small applications for each of the individual domains. Run this exercise for a week or two for each domain. Check what kind of work you are enjoying the most and this way you can decide your interest area(s). Start acquiring the domain specific skills after deciding your interest area(s). Learn concepts by practically implementing them. Don’t try to attempt all things at a time or try to acquire all the skills at the same time. Give yourself proper time to learn. Always remember that your data science related skills, your projects and your contributions remain with you forever so focus on them rather than any other things. Remember — “Acquire skills in such a way that you can be a technology creator instead of a technology user.” Those who are trying to get the job in data science field, I would like to tell them please focus on the projects and domain of the company for which you will be hired. Don’t focus on the size of the company. In long run, your projects/work-portfolio will speak, on behalf of you. I would like to tell you that if given a chance you should work on big projects at small or medium size company aligned with your interest area so that you can learn more about various aspects of the data science rather than working at big company on small chunk of a project. When you try to change your job, you will be asked what kind of work have you done so far in your current or previous company? Your potential employers won’t be much interested in your previous company’s profile or current company’s profile but they are interested in your profile, in your skills and want to learn more about you and your projects. Make sure you have great work-portfolio so that you can impress them. Advice that you should ignore is: I would ignore those who say some kind of certification in data science is really mandatory to prove your skills. I have different opinion. If you learn skills without certification and prove your skills by completing some cool data science projects then there is no need of certification. You can also enrich your skills by participating in various hackathons. VK: What is bad recommendations given in data science in your opinion? JT: According to me, there are no bad recommendations. It is very subjective matter and it varies person to person. You need to decide which recommendation will be the best suited for you. Although during initial days of my career, I got an advice from some source that you have to know all the advance concepts of linguistics if you want to learn about NLP but in reality, I just need to know basics concepts of the linguistics which can help me in my project. I don’t like when people consider role of linguists and NLP engineers in same manner. In reality, they both serve a different purpose and have a different skill-set. I also don’t like when people consider data science and data analytics in the same way. Based on this interpretation they advise people whereas in reality, they both are different terms. They include different set of sub-domains/fields. VK: How do you determine saying no to experiments/projects? JT: I always choose the project which can be helpful for the company as well as take lesser amount of time to develop. I keep the projects in my wish list for which more amount of data and extensive amount of time is needed. VK: Do you ever feel overwhelmed by the amount of data or size of the experiment or a data problem? If yes what do you do to clear your mind? JT: I usually get overwhelmed when I deal with any new dataset. In order to clear my mind I usually start doing following things. As a first step, I try to understand problem statement really well. Check what type of dataset I’m having. Whether it is structured dataset or unstructured dataset. If dataset is the structured one, then I take one table at a time and try to understand the meaning of each column. I also check what is the importance of the data column for building data science application. If dataset is the unstructured one, then I take small amount of chunk from the dataset. Analyze it. List down my findings. Now, I need to repeat the process couple of times. Every time the chunk of the data should be obtain randomly from the main source of the dataset so that I can generalize my findings. If it is possible for you then try to understand how data has been collected. VK: How do you think about presenting your hypothesis/outcomes once you have reached a solution/finding? JT: This is the challenging part for me. Especially, when the person whom you need to explain your results is not from the technical or data science domain. In that case I’m following the given steps. List down important points of your outcome ( findings, advantages and disadvantages). I also try to cover all minute but important details about the result/outcome for different types of stakeholders. I always keep things simple (minimum technical words, more layman terms) so that people can understand the outcome easily. I usually prepare the list of potential questions which can be asked to me so that I can answer them with proper logical explanation. VK: What is the role of intuition in your day to day job and in making big decisions at work? JT: Intuition helps in order to derive the basic features or choosing hyper-parameter for data science project. It also helps you to make base-line model for the project. If you have deep knowledge about the domain then your intuitive decision really helps to make big decisions. VK: In your opinion what is the ideal Organizational placement for a data team? JT: In my opinion, every company and team have their own choices and hierarchies when it comes to the placement of the data science team. Type 1: If Data Scientists who are focusing more on software engineering part of the data science projects then they should report to the Engineering. Type 2: If Data Scientists who are building new products then they should report to the product team or CEO because the features of the new products should be aligned with the overall vision of the company. VK: If you could redo your career today, what would you do? There are nothing much that I want to change in my profession journey but I really wish I would have started hosting ML projects on GitHub earlier but better late than never. VK: What are your filters to reduce bias in an experiment? JT: I usually use cross validation techniques to handle bias related issues. If you have adequate number of data samples and you want to use all the data samples present in the dataset then use K-fold cross validation. Random subsampling is more preferable when dataset which you are considering is either undersampled or oversampled. As well as if you don’t want to use all the data samples in K-1 fold then random subsampling is the way to go. VK: When you hire Data Scientists or Data Engineers or ML Engineers what are the top three technical/non — technical skills you are looking for? JT: If I’m hiring a Data Scientist who will be building data science products then following are the key skills. Strong knowledge of ML/DL Good coding skills Great learner Good communication skill VK: What online blogs/people do you follow for getting advice/ learning more about DS? JT: Machine Learning subreddit is one of the resources from where I get an idea what is currently happening in AI / ML industry. Here are some of the blogs, and YouTube channels which I follow: Twitter and LinkedIn works for you if you know who you need to follow. I like to follow top researchers from academia and industry experts on twitter and LinkedIn so that I can come to know best of both the worlds. My twitter handle is @jalajthanaki.

https://medium.com/acing-ai/simplicity-is-the-glory-of-expression-interview-with-jalaj-thanaki-ebook-giveaway-a2a82265e59d

['Vimarsh Karbhari']

2020-02-26 05:59:44.144000+00:00

['Machine Learning', 'Expert', 'Startup', 'Artificial Intelligence', 'Data Science']

IBM Cloud Transformation Advisor Wins in the 2020 BIG Business Innovation Awards

Our team at IBM Cloud is excited to announce that we have won a 2020 BIG Business Innovation Award for IBM Cloud Transformation Advisor. It’s so exciting to see our experience design work recognized for such a technically complex domain, and forward-thinking product in the space of cloud technology. The Business Intelligence Group was founded with the mission of recognizing true talent and excellent performance in the business world. This year the awards received submissions from around the world, from organizations looking to receive recognition for their most exciting innovations. The jury consisted of a carefully selected group of business leaders and executives with industry expertise in different science and science and technology fields. We’re thrilled to start off the new year strong with another award for our team at IBM Cloud. I’m proud of all the designers, researchers, developers, and managers that worked hard to create this outstanding product. What is IBM Cloud Transformation Advisor? As part of IBM Cloud Pak for Applications, Transformation Advisor (you can try it out here) is a software tool that helps businesses modernize and migrate their applications from on-premises environments to the cloud. This process typically requires a lot of preparation and an in-depth analysis of the applications being migrated. Every software application is different in terms of how up-to-date it is and how suitable it is for a cloud environment. Users first need to spend time determining the structures of their application, which parts need to be modernized, and which tools and conditions are needed in order to migrate it to the cloud. Transformation Advisor helps with assessing, planning, and executing these app modernizations. Transformation Advisor allows users to sort their applications into business applications and collections to prepare for a migration plan. The software tool performs an analysis of users’ software applications, including an evaluation of each application’s file content and structure. The tool then offers estimates for how complicated a specific application will be to migrate to a cloud environment and what issues might arise, a rating of how much effort it will take to prepare the application for migration, and recommendations for target cloud environments most suited for the application. All of these complex processes are carefully designed with a focus on simplicity and understandability, thus enabling the user to achieve success with a application modernization and cloud journey. Transformation Advisor offers recommendations for a migration and modernization plan for each application, including how complex it will be to migrate to a cloud environment. The process of migrating applications to the cloud is typically costly and time-consuming for users, as it requires in-depth resources, technical knowledge, and skills. Many businesses in these situations feel intimidated by modern cloud technology and don’t know how to approach this transition to the cloud. The IBM Transformation Advisor experience was designed intentionally to help bridge this gap in skill and knowledge, by providing users with guidance and informed recommendations on how to successfully modernize their on-premises applications for cloud environments. By being informed on these processes, users are able to make the best decisions for their business without disrupting too much of their operations, saving money and effort in the long run. Designing for a Future in the Cloud The design team behind Transformation Advisor worked through intensive user research and design iteration cycles leveraging the IBM Enterprise Design Thinking framework, to deliver a product that helps users through a highly technical and complex process. The product is monumental in helping IBM users and clients build a future for their businesses. As cloud technologies are becoming more mainstream and necessary for everyday business operations, our design team at IBM is advocating for inclusivity and accessibility by helping build bridges between our users and these seemingly high-tech systems. A modern and technologically up-to-date business infrastructure shouldn’t be out of bounds to anyone, and with the help of a well-designed software tool, we are able to bring this powerful capability to all of our users. Winning Team

https://medium.com/design-ibm/ibm-cloud-transformation-advisor-wins-in-the-2019-big-business-innovation-awards-efc791e2436a

['Arin Bhowmick']

2020-01-22 17:57:51.219000+00:00

['Design', 'UX Design', 'UI', 'Cloud Computing', 'UX']

LOL — Issue 28

Book Suggestion — A Fine Balance by Rohinton Mistry: Short Hair — Swastika Jajoo On My Last Day In Australia — Sierra DeMulder Sierra DeMulder is an internationally touring performance poet and educator, a two-time National Poetry Slam champion, a four-time published author, and the co-founder of Button Poetry, the largest digital distributor of spoken word in the world. The Wolf’s Postcript To ‘Little Red Riding Hood’ — Poem by Agha Shahid Ali Advice To Women — Poem by Eunice de Souza Sometime next week we’ll be reviewing two poetry books

https://medium.com/lol-weekly-list-of-lit/lol-issue-28-a1f74ac3c067

['Arihant Verma']

2017-08-31 14:28:14.368000+00:00

['Storytelling', 'Poetry', 'Books', 'Spoken Word', 'Lolissue']

Descent method — Steepest descent and conjugate gradient in Python

Descent method — Steepest descent and conjugate gradient in Python Python implementation Let’s start with this equation and we want to solve for x: The solution x the minimize the function below when A is symmetric positive definite (otherwise, x could be the maximum). It is because the gradient of f(x), ∇f(x) = Ax- b. And when Ax=b, ∇f(x)=0 and thus x is the minimum of the function. In this article, I am going to show you two ways to find the solution x — method of Steepest Descent and method of Conjugate Gradient. Method of Steepest Descent in Python Now let’s use this steepest_descent function to calculate With the steepest_descent method, we get a value of (-4,5) and a wall time 2.01ms. Conjugate gradient method in Python With the conjugate_gradient function, we got the same value (-4, 5) and wall time 281 μs, which is a lot faster than the steepest descent. Visualizing steepest descent and conjugate gradient descent Here we can visualize the steepest descent method and conjugate gradient method. We can see that the conjugate gradient method takes fewer steps than the steepest descent method, and thus the conjugate gradient method is faster. Steepest descent method Conjugate gradient method Hope you enjoy this article. If you are interested in the math behind the two methods, check out this article:

https://medium.com/dsc-msit/descent-method-steepest-descent-and-conjugate-gradient-in-python-85aa4c4aac7b

['Sophia Yang']

2020-12-26 05:46:37.558000+00:00

['Linear System', 'Visualization', 'Python', 'Gradient Descent', 'Data Science']

Typing DNA Command Line Authenticator

The application uses Typing DNA authentication services, a service that captures user typing pattern to authenticate the commands that a user wants to run and if verified then it let them execute them. The user gets a simple popup application where he/she can add/edit commands that needs to be verified for the specific typing pattern that of the user. Demo: Inspiration for the Project All the developers make use of the terminal while running the commands. And commands can be run by any user without verifying whether it was explicitly run by a specific user who was authenticated to do that or by anyone else. If anyone gets access to my laptop or a server the user will be able to run the command. What it does The application uses Typing DNA authentication services to authenticate the commands that a user wants to run and if verified then it let them execute them. The user gets a simple popup application where he/she can add/edit commands that needs to be verified for the specific typing pattern that of the user. How I built it It has a 6 component architecture that interacts with one another. The swift application creates a popup for ease of use which has an embedded application for angular. Angular application interacts with the Django backend which stores and persists the user information, command information, access tokens as well as interacts with the Typing DNA Apis and the PostgresSQL Database. The Swift Application interact with the Terminal and syncs up the commands that are being configured in the system. Challenges I ran into First i thought of using the swift application’s global listeners to get all typing events and pass it to the angular application which has the typing dna javascript library but the delay in the events form the computer created an abnormal typing pattern at the javascript library. Thus i changed a few bits and got the application working as seen in the demo. Accomplishments that I’m proud of Learn about the typing DNA apis as it is an interesting project. I had heard about the concept when i was in my final year of engineering but it was good to see a product working in production and learning to interact with it. I also enjoyed completing the application in due time. I got to know about the competition on 10th of October thought of an Idea but wasn’t sure would be able to complete it as i wasn’t aware about swift development and there were a lot of loop holes i saw in the development lifecycle for my application. What I learned Interacting with typing DNA. Swift application development. A little bit of bash scripting. How swift interact with the shell scripts and vis-a-versa. What’s next for Typing DNA Command Line Authenticator With some small changes in the code this can be deployed on the server and as a proper application for Mac Users. The same shell scripts and the backend can be reutilised for authenticating command requests on a server. Github:

https://medium.com/analytics-vidhya/typing-dna-command-line-authenticator-313837bdec73

['Anmol Singh Suri']

2020-11-08 17:08:33.255000+00:00

['Angular', 'Python', 'Development', 'Swift', 'Programming']

The Psychology Of Color

However, in reading this article I found that these same elements relate to communications planning — especially when itcomes to storytelling, data representation (infographics) and presentation decks. To create a truly powerful creative presentation that will capture the interest of the audience, it’s crucial to build a visual connection with your audience through color. When it comes to design, the initial focus typically lands on idea, concept and then execution. The first step typically is to draft the layout of the project. However, most often than not, we forget that design is not just about creating cool layouts or intricate designs. Design is about building a connection between the product which we are designing and the target audience. The best way to do so is through the use of color. As humans, we are naturally drawn to certain things, in large part due to the color used and the feeling it evokes. Color expresses an emotion, gives the tone and attracts a person’s attention to the overall design. “Color is an essential factor to the world of graphic design and advertising. Not only that it brings in depth and emphasis to a design but it also gives the feel and the mood of a design.” The most fundamental way to grasp the psychology of color is to first understand the color wheel. The color wheel is made up of the hues, tints, tones and shades of primary, secondary and tertiary colors. Primary colors consist of the colors yellow, blue and red. Meanwhile, secondary colors consist of green, orange and purple. These colors are the main colors used in brand identity and advertising. Bold primary colors are often used within a brand’s identity (logo). They capture the eye of the viewer, and if used consistently in the long term, they become recognizable. This is not just because of the brand name alone, but by association with brand color. For example; the following logos represented in the photo use primary colors along with minimal use of positive and negative space (the representation of white and black) for their branding. (Note: The article introduces black and white as “actual” colors. However, in design they are not considered colors. “In the visible spectrum, white reflects light and is a presence of all colors, but black absorbs light and is an absence of color. Black can be defined as the visual impression experienced when no visible light reaches the eye.”) In the case of secondary colors, some brands use them for color identity, but only some.

https://medium.com/comms-planning/the-psychology-of-color-8a54ab8a6964

['Naja Bomani']

2016-07-07 15:36:11.638000+00:00

['Branding', 'Colors', 'Design', 'Psychology', 'Advertising']

PWiC and OPEN Seattle: Making the Leap to Startup from Corporate Life

OPEN Seattle After the networking event, Azfar Moazzam for OPEN Seattle welcomed the attendees and gave an overview of the goals and vision of OPEN Seattle. He reminisced about the early 90s when there were not many Pakistanis living in Seattle and expressed his excitement about how the community has grown thus far. He mentioned that OPEN’s membership boasts leading entrepreneurs, business leaders, and corporate professionals. There are currently 13 OPEN chapters globally and it hosts dozens of networking, knowledge sharing, and mentoring events every month. Azfar Moazzam — OPEN Seattle PWiC After Azfar’s presentation, Huma Hamid, PWiC President, and Co-Founder introduced the global community to the audience and shared her story of PWiC inception. She impressed the attendees with the great number of successful partnerships that PWiC has created and the tremendous impact that it has made throughout the years. Huma Hamid, PWiC -President & Co-founder Keynote Session By Farrukh Malik The keynote was delivered by Farrukh Malik, CEO, and Co-Founder at Discretelogix | President OPEN Islamabad, who was on a business trip to the US. Farrukh is a seasoned Pakistani entrepreneur with multiple startups and technology initiatives under his belt. In his keynote, he shared his personal journey of becoming an entrepreneur and the current ecosystem for technology related startups in Pakistan. Farrukh Malik, CEO, and Co-Founder at Discretelogix | President OPEN Islamabad Panel Discussion Next, Alishba Khawaja moderated the panel discussion on the topic of entrepreneurship. There were four panelists from a diverse type of businesses: Farrukh Malik — CEO and Co-Founder at Discretelogix | President OPEN Islamabad CEO and Co-Founder at Discretelogix | President OPEN Islamabad Afshan Abbas — CEO and Founder at Fuchsia Shoes — CEO and Founder at Fuchsia Shoes Fahim Ul Haq — CEO and Founder at Educative.io — CEO and Founder at Educative.io Raja Iqbal — CEO and Founder at Data Science Dojo The panelists went over topics ranging from productizing and financing a startup to setting up the right culture for your company and hiring your first employees.

https://medium.com/pwic/pwic-collaboration-with-open-seattle-2bb67e449cfa

['Pakistani Women In Computing']

2019-07-23 04:01:50.365000+00:00

['Pakistan', 'Startup', 'Pakistani']

5 Habits of People With Very Low Emotional Intelligence

5 Habits of People With Very Low Emotional Intelligence These are the behaviours you want to avoid to build better and meaningful relationships In a very practical sense, we have two minds, one that thinks and one that feels. Highly emotionally intelligent (EI) people rank high on responsiveness, empathy, listening, and self-awareness. And they excel at interpersonal interaction. The reason emotional intelligence is so widely valued is pretty simple. It plays a role in everything. The ability to manage your emotions, as well the emotions of others is an important skill to master in the 21st century. In Emotional Intelligence: Why It Can Matter More Than IQ, author Daniel Goleman argues that “People with well-developed emotional skills are also more likely to be content and effective in their lives, mastering the habits of mind that foster their own productivity; people who cannot marshal some control over their emotional life fight inner battles that sabotage their ability for focused work and clear thought.” People with very low emotional intelligence cannot accurately perceive emotions in themselves and others. They are also usually judgmental, and self-destructive. They can be difficult to get along with on a personal or social level and difficult to work with because they cannot respond positively to even the most constructive or well-intended criticism. People with low emotional intelligence have a lot of things in common. 1. They don’t develop meaningful relationships Everyone needs meaningful relationships to thrive and to avoid traveling through life alone. When someone has very low emotional intelligence, they tend to navigate the world alone because they find forming friendships — especially meaningful and lasting friendships — difficult. Good and lasting friendships are formed through the mutual exchange of ideas, exhibiting empathy and compassion, offering support to the people we care about. People with low emotional intelligence don’t provide the appropriate connections and responses to those close to them. Hence they miss out on the opportunity to make meaningful connections. That can mean self-imposed isolation. You can break the pattern of low intelligence in yourself by getting to know other people better and resisting the temptation to talk more than you listen. 2. They are not self-aware Emotionally intelligent people have a candid and realistic understanding of themselves. People with low emotional intelligence, on the other hand, lack emotional awareness. They don’t understand how their emotions influence their behavior. Emotionally intelligent people are in tune with how they feel, but they do not let their emotions rule their lives. They are mindfully present when responding to situations. Genuine introspection and truly knowing oneself can help you develop self-awareness, compassion, social intelligence. 3. They are self-focused Because people with low emotional intelligence cannot process or understand the emotions of others, they tend to draw every conversation, circumstance, and situation back to themselves. They seem to live out the adage — been there, done that — and have a seemingly valid reason to steer every topic back to them. They also tend to take over conversations and ask rhetorical rather than open-ended questions because the question is usually intended to grab or keep your attention, not to hear your response — or even to give you the opportunity to make one. People with very low intelligence cannot truly open themselves up to being fully available to others, but usually will not give others the opportunity to open up, either. They are often manipulative, calculating, and inherently controlling. You can break the pattern of low intelligence in yourself by honing your listening skills, and by learning to actively engage with others with your ears, not your mouth, wide open. 4. They are never wrong Like most of us, you probably know someone who has an opinion on everything. In fact, they usually think they have the only opinion that matters. This is a trait of someone with very low intelligence. In fact, they will frequently argue with others because they want to force or sway them to their point of view. Dealing with argumentative people like this can be a frustrating experience because they listen to speak, not to hear, so they refuse to acknowledge anyone else’s right to have an option that differs from their own. People with very low emotional intelligence are usually staunchly convinced that they are always right and will argue until the end of time rather than concede even a single point in an argument. They are usually unsympathetic, cannot empathise with others, and can sometimes be perceived as bullies. When someone has low emotional intelligence, they tend to eschew emotions and have trouble managing theirs and interpreting yours. You can break the pattern of low intelligence in yourself by learning to see, hear, and feel the emotions of other people and by learning to shape your own responses and reactions accordingly. 5. They are never at fault When someone does not have a handle on their emotional wellbeing, they typically never accept blame for anything. A low score on a test is the fault of the instructor or of a perceived flaw in the exam. A job loss is the fault of lousy coworkers or of a boss who does not understand them. Mistakes are how we learn, and everyone makes them. When someone can never admit a mistake, it also means they can never learn from it and are likely to make the same mistake — and blame the same scapegoat — over and over, again. You can break the pattern of low intelligence in yourself by acknowledging a mistake, deciphering your part in it, and finding the lessons in them. People with low emotional intelligence can also be oblivious and unsympathetic, indignant and self-righteous, and can often seem impossible to please. The key to learning to develop a high emotional intelligence quotient is in knowing you lack one in the first place. The good news is, your emotional intelligence is completely under your control. You can improve it and get better at understanding people’s emotions and relating better with them. If you find yourself in the constant company of a friend, family member, or colleague with low emotional intelligence, you can help them grow and develop into an emotionally intelligent person — a change that can be mutually beneficial for all concerned.

https://thomas-oppong.medium.com/5-habits-of-people-with-very-low-emotional-intelligence-92008352aad6

['Thomas Oppong']

2020-09-03 21:03:31.900000+00:00

['Relationships', 'Lifestyle', 'Mental Health', 'Self', 'Psychology']

Want to Read People? Start by Reading These Books

People are tough to read. A few years back I went to visit my family at Christmas. I was supposed to get back in the city the next day. However, my family insisted me to stay. So I called my then-girlfriend. I asked her if it was okay with her for me to return after the new year. She understood that I hardly got to spend time with my family and complied. Later, as I got back to the city and visited her, she showered me with the fire of absolute rage. Apparently, when she said yes, she meant no. Well, that made almost as much sense as QAnon conspiracy theories. Later along the way, we split ways, and I started dating another girl. Then in some similar turn of events, again, I had to stay longer in my hometown than I expected. So I called my current girlfriend to inform the new development. This time she, herself, expressed her unwillingness to go out and told me not to worry about it. I appreciated her for being understanding of my situation. Besides, I found her appetite for laziness amusing. However, a few weeks later, during an argument, she too mentioned my failure to decrypt her straight forward yes as a no. By the time I had spent two and a half decades with the species of Homosapien since my parents — let’s not go there. What I am trying to say is, I felt clueless. I felt like an alien, looking at the grand pyramid, trying to figure out why the people from earth accuse them of building it. So like any other nerdy entity, I fell back on books to find some answers. Chances are you are not as bad of a spouse as me. Yet, you may have a fair share of troubles reading people. Still, it is something that we need to master to thrive on this strange planet, both professionally and personally. Just think to yourself. How many times did you felt like you understood what your editor meant only to get more red marks and notes on your piece? Being able to read people beyond their words comes with an enormous advantage. It helps you to cut through the noisy cloud of expressions, allowing you to see where the other person is coming from in a conversation. So here I am listing three books that will help you understand people better.

https://medium.com/books-are-our-superpower/want-to-read-people-start-by-reading-these-books-b77f139ce13f

['Anirban Kar']

2020-12-25 10:06:58.762000+00:00

['Books', 'Self Improvement', 'Psychology', 'Life Lessons', 'Reading']

Data Science Reading List for September 2020

Data Science Reading List for September 2020 Books, research papers, and blog posts I’m reading in September. 📚 Note: I am not affiliated with any of the writers in this article. These are simply books and essays that I’m excited to share with you. There are no referrals or a cent going in my pocket from the authors or publishers mentioned; I prefer to align my incentives with the reader rather than the publishers. Reading is a vitamin for the brain; please support your favorite writers and enjoy! Another month of our Data Science reading list! // Photo Creds: Unsplash Welcome to another month of our Data Science reading list! We do these each month, and I love all the positive feedback. I especially like when folks share their own recommendations. Feel free to share your own books, blogs, and anything else you’re reading this month. I would be happy to give your favorite authors a read and maybe include them in a future list! luke [at] spawner [dot] ai On to this month’s list! Building Machine Learning Powered Applications: Going from Idea to Product O’Reilly has partnered with a bunch of really high quality Data Scientists and Machine Learning Engineers recently to spit out some high signal to noise reads. This one is no exception. Our author goes the full scope of Machine Learning Engineering, covering all the way from project inception and planning to training, deploying, and monitoring. This is the exact type of important information sharing we have been missing over the last decade in our field. This engineering perspective is perfectly aligned with the evolution of the role of Machine Learning Engineers. Big ups to the author for a great reference and read! LINK Life in Code: A Personal History of Technology Life in Code by Ellen Ullman is a unique view from her time starting in San Francisco in the 70s as a software engineer and working through the rise of the programmer and technology. Ullman lays out much of the evolution of tech, from culture to code. Reading this reminds me of piecing together chats from all the senior engineers and leaders who have told me stories and historical tidbits from their early days in tech. Spectacularly fun read. LINK Scientific Freedom: The Elixir of Civilization Whether you agree or disagree with the author’s arguments, Scientific Freedom raises important points about the role of science and its place in our civilization. Braben discusses the pitfalls of funding and peer review, and he discusses a fresh model for research and the reinvigoration of scientific discovery. This is an updated version to the first edition published in 2008. Beset with beautiful formatting, well-done charts, and more. Big ups to Stripe Press for its continued efforts to publish and highlight important writing. LINK

https://towardsdatascience.com/data-science-reading-list-for-september-2020-15edcd4f4a9e

['Luke Posey']

2020-09-22 19:02:34.748000+00:00

['Technology', 'Startup', 'Books', 'Reading', 'Data Science']

How Many Times Have You Broken the Law? What You Need to Know About Copyright

How Many Times Have You Broken the Law? What You Need to Know About Copyright Lisa Walton Follow Oct 11 · 9 min read Photo by Markus Winkler on Unsplash Small business owners have a lot on their plates. Inventory and invoicing. Customers and employees. Revenue and taxes. Updating your website. One of the last things you are likely thinking about is copyright law. But copyright issues often arise in small businesses. Especially in the context of websites and other marketing efforts. As a small business owner, copyright may affect you as both a creator and user of protected work. Looking for pictures for your home page? Need some content for your blog? If you are just copying and pasting from other sites, you are violating copyright law. And that could get very expensive. If you run a creative business, you need to make sure you protect the work you post on your website. Or you could be losing valuable revenue. Like many areas of the law, copyright rules are extensive and complex. But this article will cover the basics to help you steer clear of infringement. What Is Copyright? Copyright law governs one’s rights and ability to use another’s creative work. It including writings, drawings, photographs, paintings, music, and software codes. Copyright law promotes creation by giving authors exclusive property rights in their works. If you own the copyright to something others may not use it without permission. Copyright usually belongs to the creator of an original work. The author who writes the book. The artist who sculpts the vase. The musician who writes the score. But copyright can be sold, traded, or inherited. Works created on commission often vest the copyright in the patron, not the creator. Publishing companies and recording agencies often hold the copyrights to works they produce. What Can You Copyright? Copyright protection extends to an “original work of authorship”. There are three requirements for works to copyrighted. They must be: original, “fixed in a tangible medium of expression,” and possessing a modicum of creativity. Original means that work did not exist before the artist created it. Copyright protects works of artistic creation, including: Music — songs, arrangements, scores, recordings, etc… Writing — novels, poems, stories, journalism, plays, blog posts, etc… Visual art — painting, drawing, photography, sculpture, etc… Dance choreography Movies Computer software Architecture. Copyright protection only applies to works that have been set into a “fixed and tangible” form. You cannot copyright thoughts and ideas. You must reduce amorphous concepts to a tangible expression. What Does “Fixed in a Tangible Medium of Expression”? Suppose you own a bakery. You make Tik Tok videos about cupcakes to market your products. You always create your dance moves in your head before you perform them. At this point, the dance is an idea. You cannot copyright it. Then, you practice your dance in front of the mirror making sure you get it right. This practice is not in a “fixed and tangible form” either. While you rehearse your baking competitor watches through the window. She copies your exact moves and beats you to Tik Tok. You want to sue. Not so fast... Yes, she stole your idea. Yes, she is evil. But no, she did not infringe on your copyright. Your dance is not protected until it is in a tangible form. For dance, this is a video recording or a precise written description in text or dance notation. A performance or rehearsal is not protected until it is recorded. Let’s look at another example. You own an Occult book store. You have an idea to write a poem about ghosts you encounter throughout your day. You title your poem “A Dance with the Shadow People” and post it on your website. Copyright protection attaches to your work. Two days later, a rival bookstore owner publishes a poem on her website. It’s called, “The Spirits Within Me,” and it’s about ghosts she sees in her shop every day. You see her poem and are steaming mad. You want to sue for copyright infringement. As a legal matter, you can’t sue unless you registered your copyright. See How Do You Get a Copyright? below. But even if your work were registered, there is no violation here. Although you both wrote about the same idea, ghosts in our midst, you each wrote different poems. You own your poem. Not the idea. There are lots of poems about ghosts. What Isn’t Protected? The following things are not subject to copyright protection: Data/facts Works of the federal government (memos, rules, documents, reports) Website names (which is why you should always buy .com, .net, .org, .ca) Blank forms Lists of ingredients, like recipes or formulas Names: individual names, group names, business names (may have Trademark protection) Slogans, mottos, catch-phrases Laws: cases, constitutions, statutes, regulations, court decisions Clothing, including fashion design Jokes Titles Things with utilitarian purposes, like appliances or tools (Trademark or Patent protection may be available) How Do You Get a Copyright? It’s easy to get a copyright. In fact, you don’t have to do anything to protect your creative work. Copyright is automatic. There is a myth that copyright is something you must apply for from the government. This is not true. Copyright happens automatically. Once you set your work into fixed form copyright attaches. This is true even if your tangible form is doodled on a legal pad or jotted on a napkin. You do not have to do anything more. What about that © symbol? You no longer need to use the © symbol. The copyright symbol carries no legal weight. It is not required to protect your work. The purpose of the symbol and dated copyright notice is to let others know that the work is protected. The notice provides information about the date and owner of the copyright. This information is helpful for someone seeking permission for use. Copyright notices are not required, but they are useful. The proper way to include a copyright notice is: © Date of creation, name of the copyright holder You can include additional information after the notice. Some add “All Rights Reserved” to let others know they cannot use the work without permission. Others might include “Creative Commons release”. This allows works to become part of the public domain. Should I Register My Copyright? You do not have to register your copyright, but you may wish to do so. There are three reasons to register copyright: establish yourself as the copyright owner; establish the date of creation; and to take legal action against someone who infringes on your copyright. In most jurisdictions only registered copyright owners may sue for infringement. Whether this is important to you will depend on the nature of your business and your work. If you sell original paintings or write bestselling novels, you’ll want to register your works. If you are writing blogs about shampoo or producing flash fiction every day, you don’t need to. You may also want to register your copyright if you can’t otherwise prove the date of your creation. This often applies to unpublished works. The date of creation is important for copyright disputes. Remember, copyright only protects original works. If two people claim to have written the same movie, the person who did it first owns the copyright. It is easy and inexpensive (only $35) to register a work online. You do not have to register copyright right away. If an infringement occurs and you want to sue, you can register at that time. The processing time for copyright registration filings can take a year. So, if you go this route you need to act quickly. The statute of limitations for copyright infringement is three years. You must file suit within three years of when the infringement occurred. What is an Infringement? When someone uses your work without permission they have infringed on your copyright. Examples include: downloading music sharing software posting photos photocopying books or lessons singing someone else’s song The unauthorized use of images is a common example of copyright infringement. And one that many business owners commit. To win a claim of copyright infringement you must prove the following: You are the owner of a valid copyright in the work or have the legal authority to bring a lawsuit; the defendant actually copied the copyrighted work; and the copied sections are protected by copyright (not merely facts that exist in the copyrighted work). Evidence of actual copying of the work can be proven directly or indirectly. It’s uncommon to have proof of someone directly copying your work. Instead, you can show the infringer had access to the work and their creation is “substantially similar to the copyrighted work.” Access is easy to prove in the case of a public website. You can show that the defendant’s work is “strikingly similar to” the copyrighted work. There must be a tangible loss to recover money. You have to show that by copying your work the defendant caused you to lose money. If you prove a financial loss, like lost profits, you can recover actual damages. Most copyright cases settle out of court. The typical remedy is an order to remove unauthorized material. What About Fair Use? Fair Use is a defense to a copyright infringement charge. In the U.S. we have a First Amendment guarantee to free speech. This means, subject to some restrictions, we can say what we want. Copyright law restricts free speech. Fair Use is the solution. Fair Use allows the use of copyrighted material for commentary, criticism, or parody. Unfortunately, there are no bright-line rules governing Fair Use. This is a gray area of the law. Judges use a list of four criteria to determine whether a specific instance is a Fair Use. They consider: The purpose and character of the use, including whether such use is of a commercial nature or is for nonprofit educational purposes. The nature of the copyrighted work. The amount and substantiality of the portion used in relation to the copyrighted work as a whole. The effect of the use upon the potential market for or value of the copyrighted work. The context of the use is important. If you use copyrighted photos on mugs and t-shirts that you sell for a profit that is likely an infringement. You are illegally using someone else’s work for commercial use. But, if you use copyrighted photos in an article celebrating local photographers that may be Fair Use. Especially if you include links to their portfolios. The “nature of the copyrighted work” considers the cultural importance of a work. It also evaluates its newsworthiness, and whether it is a published or private work. If the news is doing a story on art theft, they may show photographs of stolen paintings. The amount of the work used also matters. A snippet of a poem or a paragraph or two of a 300-page novel or a 15-second clip of a performance is usually permissible. But if someone records all but the first five minutes of a movie and releases it on YouTube, that is likely infringement, The last factor asks if the unauthorized copy diverts sales away from the original. Small excerpts included in a positive review may increase the work’s value. This is Fair Use. Negative criticism can also be Fair Use though. If the review uses a small part of the work for critique or commentary it is permissible. Even if it adversely affects market value. The criterion asks whether the copy is a valid substitute for the original work. Fair Use is a confusing and complicated area of law. You should never rely on Fair Use to excuse your unauthorized use of others’ work. Instead, you should search the public domain for content. What is the public domain? The “public domain” refers to creative materials that are not protected by copyright. No individual author or artist owns these works. Rather, they belong to the public. Anyone can use a public domain work without obtaining permission, but no one can ever own it. Work falls into the public domain in one of four ways: The copyright has expired. As a general rule, copyright lasts for the life of the author plus 70 years. It expires at the end of the calendar year. The author failed to follow the copyright renewal rules. The author intentionally assigned the work to the public domain. This is called “dedication”. The work is not protected. You can find public domain images at Unsplash or Pixabay. Music is available at https://www.pdinfo.com. As a small business owner, the public domain is your best friend. If you don’t want to pay for images or other content, make sure you are searching in the public domain. Take your time. Do your research. Make sure you have the right to use images, text, video, and audio clips. Don’t rely on Fair Use to absolve you of liability. Disclaimer: This article does not constitute legal advice. This Q & A provides general information on the issues covered. It is not intended to be a comprehensive summary of all laws which may apply to your situation. Please consult your own legal advisor regarding the specific application of the information to your business.

https://medium.com/swlh/how-many-times-have-you-broken-the-law-what-you-need-to-know-about-copyright-5ef173e9a241

['Lisa Walton']

2020-10-19 19:26:09.708000+00:00

['Writing', 'Copyright', 'Entrepreneurship', 'Law', 'Small Business']

What Your Anger Is Trying to Tell You

What Your Anger Is Trying to Tell You There’s a thin line between rage and fear — especially in times of uncertainty Photo: Jennifer Walsh/Flickr Everyone has their own way of loading the dishwasher. Some delicately arrange; others cram. Some lay large utensils perpendicular to the tray; others go parallel. Regardless, we can all agree that this is just not a big deal. So earlier this week, when I reached over my wife’s shoulder and adjusted a cup, then a bowl, I knew I was basically picking a fight. But her response concerned me more than any quick rebuke would have. Instead of telling me to fuck off and do something useful, she said, “I’m sorry.” And worse, I realized she’d been apologizing a lot over the last few weeks of sheltering in place. For the dishes. For noise while I’m working. Even for the dogs, as if they’re her responsibility alone. Why was I so concerned about this pattern? Because as someone with anger management issues, I’ve learned over time that when a loved one begins to apologize more frequently than is necessary, the problem is usually not them — it’s me and my anger. I don’t think I’m alone in noticing the eerie way being cooped up has the potential to get ugly — even when the people we’re surrounded by are those we love. Unchecked, minor irritations can become major problems. Nits to pick are becoming nuts to unpack. Pet peeves are growing into… full-grown peeves. Anger and isolation Hidden in the deluge of Covid-19 news stories are other, not unrelated, stories of the dangerous impact isolation, quarantine, and imposed immobility may be having on our mental and physical health, especially for people in already abusive relationships. António Guterres, the secretary-general of the United Nations, released a short video on Twitter about the dangers for women and children trapped in their homes with abusive partners. The New York Times ran a piece about what first responders at the National Domestic Violence Hotline are seeing, which is predictably grim. Even for those of us who don’t fit the definition of “abusive partner,” the current situation has some risks. Yet there’s a tendency to not treat it seriously. On April 5, New York Gov. Andrew Cuomo introduced the topic of cabin fever during his daily update. Though he was quick to point out the condition has no official diagnosis, he characterized it by feelings of isolation, mood swings, resentment, and irrational outbursts. The governor prefaced this segment with the phrase “on a lighter note.” To be fair, it’s lighter than the subject of intubation, but it’s symptomatic of the somewhat confusing relationship with anger we hold as a culture. We’re taught to bottle it up, to “manage” and “control” it. We learn from books and movies that getting angry is a character flaw. But it’s also linked to power and success and is often rewarded. What is anger? It’s easy enough to find a definition of anger, but by singling out the feeling of it — annoyance, displeasure, hostility — we’re missing the complete picture. Tidy dictionary definitions don’t do justice to an experience that, once unpacked even a little, proves to be startlingly nuanced. Recently a friend who works for the federal government let loose on a group email thread we’re both on. Stuck in Washington, D.C., under quarantine, she was gripped by fear for her own safety, frustration with her lack of power, and rage at what she saw as an incompetent governmental response to the pandemic. At the end of her rant, she apologized, explaining, “I am just so fucking angry all the time.” How can the same feeling arise over a misplaced dish in the dishwasher and in response to something as serious, and abstract, as political incompetence? What a purely phenomenological definition fails to account for is that the experience of anger can seem fundamental, mystical, and complex. Counselor, coach, and author of Anger Among Angels, William DeFoore, PhD, prefers to use the following definition as a leaping off point: Anger is the emotion that comes when you’re threatened or opposed in any way. This is still based in feelings, but here at least we begin to see its fundamental connection with the world — whether external or those parts of yourself you can’t seem to control. The evolution of anger This might sound obvious to scientists, but anger researcher Ryan Martin, PhD, reminds us that anger, like any emotion or behavior common to all humans, exists today because it proved to be an evolutionary advantage. In a 2018 TEDx Talk, Martin suggested, “Just as fear alerts you to danger, anger alerts you to injustice.” Since anger is commonly thought to have origins within the fight or flight mechanism meant to save our lives, Martin’s description is useful in delimiting it from fear, though of course both can be caused by danger. By invoking the idea of injustice, it becomes a little clearer how small, petty grievances can share a term with such vast, serious ones. The fact is that whether the injustice is minor or major, our response to it is weighed against an estimation of how things should be — and in this way, anger becomes highly personal. What might anger one person can leave another completely unfazed, even approving. Like, oh, I don’t know, a president’s response to a crisis, for instance. This understanding of anger has deep roots. Though Aristotle never wrote a treatise on anger specifically, he wrote about it at length throughout his other works, notably in Nicomachean Ethics and Rhetoric. He observed that, singular among the emotions, anger was tied up in ideas of right and wrong, and therefore in addition to a psychological dimension, it possessed an ethical one. What anger looks like If you took philosophy in college, you might remember that, for Aristotle, “virtue” was always the mean between two extremes. The virtuous person chose the middle path in all things. They didn’t eat too much, for instance, but they didn’t starve themselves either. Anger was of particular interest to Aristotle because it seems to go hand in hand with excessive feeling or action. It’s often tied, in other words, to the experience of losing control (akrasia in ancient Greek). One of my clearest memories of my teenage years was of being caught in the stairwell by my father, of him holding me against the wall and pulling back his fist. My father never actually hit me, but even at the time, I completely understood what he was feeling. Between the ages of 10 and 16, I hummed with a constant, fluttering panic that would build steadily until some proverbial straw — often at the unwitting hands of my younger brother — would unleash a torrent of hateful words and physical violence. It would scare my brother, it would scare my family, and it would scare me. Midway through my teens, however, I learned an interesting trick. I would monitor the anger as it was building, and before it reached a boiling point, I would swallow it. Psychologists call this suppression, which has itself been studied and is thought to cause or contribute to a variety of other ailments, even physical ones. At the time, however, I was thrilled by this personal discovery. It made me feel like I was in control, and the satisfaction of seeing others respond to my rage was replaced by the pleasure in having a secret, in knowing what I could do or say. In talking about this essay with my brother a few days ago, he said, “Funny, I don’t consider you an angry person.” My wife might disagree, but it’s true that my anger no longer often takes on a form people might readily associate that way. After learning to suppress it, I began to express it as hyper-nit-pickiness, a rapid broadcast of critical observations and insults. This is a shitty tendency, and over time, it has tested the limits of my romantic relationships, friendships, and professional relationships. And it turns out, I may have been better off just getting angry because there’s evidence suggesting that kind of display helps people get ahead. Rewarding anger If anger is often tied to the experience of helplessness, the feedback the world gives us when we’re angry can be unexpected. According to DeFoore, our very early experiences of anger provide an example of this counterintuitive observation. I’m talking about tantrums. What can be more unjust, subjectively speaking, than not getting exactly what you want — and being entirely unable to communicate your needs? For DeFoore, although the child is blameless for their excessive feeling, parents are often guilty of teaching them the wrong things through their response to tantrums. “Children who throw temper tantrums often get rewarded,” explained DeFoore, “because they don’t have to do the thing that they don’t want to do.” But the rewards don’t end when we’re still in high chairs. Stanford University social psychologist Larissa Z. Tiedens, PhD, found that people who express anger often receive a bump in social status. In a study published in the Journal of Personality and Social Psychology in 2001, Tiedens found that “participants supported President Clinton more when they viewed him expressing anger about the Monica Lewinsky scandal than when they saw him expressing sadness about the scandal.” Perhaps, we learned a little too much from those tantrums we threw. Anger and control As we’ve seen, the idea of anger has been caught up in the idea of control from Aristotle onward. Though anger doesn’t preclude self-control per se, it certainly reduces our capacity to think or act rationally. It’s also heightened in situations where control, or its corollary freedom, is already at stake. Think of driving. Road rage is one of our most potent and common experiences of anger. Cars are supposed to be tools of enablement, empowerment. They symbolize freedom, which is the ability to control our destiny. When that freedom is compromised, let alone undermined entirely, anger is right there to lend a hand. So what happens when it’s your entire life, not just your trip to the store, that’s been hijacked by powers beyond your control? These days, everything seems aligned to make people angry and to make angry people irate. Our wills are opposed. We feel helpless. Our fight or flight instincts are being triggered, but flight is off the table. Many of us — most likely men, most likely white — have been rewarded throughout life for angry displays. This makes for a potentially toxic environment. Tragically, there’s a growing number of people falling victim to serious domestic abuse, and because the hotlines are overburdened, services are drying up, and opportunities for escape are discouraged, that tragedy is ongoing. As Katie Ray-Jones, chief executive officer of the National Domestic Violence Hotline, told the New York Times, victims are in jeopardy “any time an abusive partner may be feeling a loss of power and control.” Right now, that describes all of us. But even short of criminal abuse, I think there’s reckoning to be done. Recognizing, interpreting, and addressing anger is something we all have to face at certain points throughout this period of social distancing and confinement. But what does that mean, and where do we start? Anger awareness The first step, like most first steps, is awareness. As G.I. Joe told a whole generation of Americans in the ’80s, “Knowing is half the battle.” If you think this seems asinine, check yourself. DeFoore recommends that anyone who is struggling with anger should start with the information readily available online. To be sure, there’s a lot there. So much, in fact, that it can be hard to navigate, to distinguish the relative validity of sources. But I’ve found that the process itself of searching, the investigation, has at the very least a palliative effect — perhaps even a healing one. Being aware of the many different ways anger can be experienced and displayed has the effect of incrementally attuning you to your own emotions. This isn’t about suppression. As DeFoore explains, that can lead to depression, which can deplete immune function. Just what you need with a deadly virus floating around! There’s a difference between suppressing anger when it rises up and trying to be mindful about what sorts of “injustices” are causing it in the first place. Do I really care about how the dishwasher is being loaded? Do I think yelling at the dogs is going to recode their DNA and make them docile and mature? Learning about anger and paying closer attention to our triggers begins the process of reevaluating our sense of justice, feelings of entitlement, and preconceptions about how things should or should not be. The positive side of anger We’re accustomed to thinking of anger as negative, violent thoughts, feelings, and behaviors. But theorists and researchers like DeFoore and Martin seem to agree that anger can also be channeled into positive action. If it’s born of a feeling of injustice, couldn’t it spur one into some sort of activity that attempts to right the wrong? Theoretically, I get it. There’s anger behind all protest, behind all social and political action. It’s fueled everything from manifestos to revolutions, and there’s no doubt the anger felt today by people, like my friend in D.C., will lead to positive change in the months and years to come. But pushing too far into this right now may sound impractical, or worse, judgmental. Like those cloying voices out there telling us to take advantage of our unexpected “free time” by learning a new skill. Practice your Spanish! Teach yourself to sew! Read War and Peace! Gah. As someone just struggling to survive, this kind of encouragement can easily come across as admonishment, and it makes me want to raise a big fat middle finger. But then, that might just be my anger getting the best of me. The practical approach is to return to that “fight or flight” idea — that anger is never far from fear. Are you being alerted to danger or to injustice? Very likely, these days, you’re being alerted to both. But it’s okay to be afraid, and if you start to feel angry, it’s okay to admit that it might be an easier way of saying you’re scared. My hope is that this thought might help bring us together rather than pulling us further apart.

https://humanparts.medium.com/how-to-unpack-your-anger-9601091373eb

['Shya Scanlon']

2020-04-18 13:59:01.539000+00:00

['Relationships', 'Life', 'Self', 'Psychology', 'Coronavirus']

Transparent & Black: Sparking a Movement for Black Healing

I’m often asked how I found the inspiration to create a card game that teaches people about bias. I say that I’ve always been open to looking inward for ways to improve, regardless of what I might find. The last 12 months of looking inward have taught me to find and investigate my traumas. An idea I will continue to explore; and one I will continue to share with Black and Brown communities and beyond. Because past the pain lies purpose, passion, and pleasure, as I am continuing to find out. Empathy For Those Who‘ve Experienced Trauma Have you ever seen someone you love bleeding from a gunshot wound? Have you ever been told you didn’t deserve a job or spot in a school because of your race? Have you lived your life without ever having a loving relationship with either of your parents? Or two or more of your grandparents? Have you ever felt sadness or shame because you aren’t sure where your lineage comes from? I have. If you’ve answered yes to any of these questions I offer you empathy, because you too have experienced trauma. Photo by Clay Banks on Unsplash Trauma is real for many Black people in America. As forced migrants from the continent of Africa through slavery, we’ve been victims of a bloody, centuries-long struggle for equal access and opportunity for physical, societal, economic, and mental freedom and safety. We grow up experiencing overt and microaggressions. Many times externally originating. And many times originating right in our own homes. Trauma experienced for so many generations that it would almost be deemed normal. This is paired with a loss of written and oral culture, as many of our elders (mine included) were so eager to rise above their past that they forgot to mine those experiences for the stories that illustrate the resolve it took for them to survive. The resilience that we’ve developed is a superpower. One used to overcome inequalities that still exist; as well as the challenges that we all face. Yet too little attention is placed on this disproportionate burden that our Black and Brown people face. A Movement Of Voices For Collective Healing As societal attention has been forced inward to what we value most. Health, well being, and community. I am proud to be a part of a movement of Black and Brown voices, and their allies, contributing to collective healing. My card game, Actually Curious, is a tool for spreading empathy. But it’s also secretly a gateway drug to talk therapy. For $25 and the intention to be vulnerable, it helps people to tell stories that need to be told in order to heal. My personal journey through healing has led me to renewed confidence, passion, focus, and purpose. I need money for the machine to work. But my motivation is to use my skills, access, and resources to positively affect issues of access and knowledge around mental health in Black and Brown communities. The long term reward is in the lives I affect. And that pays dividends today when I meet amazing partners like Transparent & Black. Image Source: Camille Shaw for Transparent & Black Wellness Is Not Something New to Black People In their words, “The global wellness market is now valued at $4.75 trillion. Many of the ingredients, spiritual rituals, and wellness practices that the industry benefits stem from BIPOC communities. We need spaces where we can unlearn this idea that wellness is something new to Black people. Our history shows us that we acted as healers, doctors, midwives, and spiritual guides long before wellness had a name, and we need spaces to honor that work and feel empowered to explore the necessary physical, mental, emotional, spiritual work needed.” All boats rise with the tide. Supporting Black healing means more unity, collaboration, and focused energy toward our shared values. The need and the demand for Black healing spaces and products exist. And we know from years of the velocity of investment in wellness, with healthy profit returns, that the market for investment also exists. One strategic partnership with the right brand or organization could finance all of Transparent & Black’s funding needs while reaping returns in content, engagement, sales, and brand love. Allyship is the easy part. Removing barriers to yes is where you need to begin.

https://medium.com/curiosity-lab/transparent-black-a-movement-for-black-healing-b7d3a744875f

['Michael A. Tennant']

2020-10-17 14:10:33.736000+00:00

['Healing', 'Mental Health', 'Wellness', 'Trauma', 'Black Lives Mater']

Want Peace? Build Your Life Around Your Spiritual Practice

And never the other way around As I mentioned yesterday, life has lately felt like walking up Mt. Everest in cement boots. With cast iron cylinders on my head. In the rain. And yet, one thing has kept me consistent and calm despite the world seemingly seeming to fall apart around me — and that is my spiritual practice. Every day, whether I feel like it or not, I get out of bed, hit my knees, say a prayer, grab some tea and do my Morning Pages. (More on this another day! In simplest form, they are 3 pages worth of free flowing writing to get your grr out at the beginning of the day so you can feel fresh, balanced and ready for new adventures to begin.) When my writing is complete, I do 5 minutes of meditation with my husband (a miracle in and of itself) and then we do a spiritual reading. When that is done, I read my own devotions and, if there is time, I’ll do ten minutes of meditation myself. This whole routine takes about 1 hour. And while, yes, I could use this time to finish up some house cleaning, move ahead with paperwork or scroll through Social Media, the bigger question is, “Why?” I have found that unless I am centered — allowing the God of my understanding to connect with the most sacred part of me where my creativity, love and true being live, I view life only through a lense of fear and anxiety. Keeping a small routine allows me to stay anchored when the storms of life blow all around me. And, unlike much of my younger days when my happiness depended on other people, places and things, keeping a practice reminds me to count on one thing and one thing only: God. God is Not Weakness Reliance on the God of my understanding does not make me a little woman, content to just sit around and let success pass her by. Do I want my musical to sell? Yes. Would I love Covid to be over so I could finally use my Disney passes and hang out with my friends in a beautiful cafe and watch babies in ridiculous outfits shriek in delight at oversized park characters? Of course! But if the spirit I bring to this job or event is restless, irritable and discontent, why would it matter if Covid ended and I could go to such an event? I wouldn’t enjoy my time there and, more importantly, I wouldn’t be of service to those around me. Anger, like a virus, is contagious, too. Focusing on the Inside Simply put, when I don’t take quiet time in the morning with God, I focus on the outsides of life, then try to control people, places and things to fix my insides. This never works. Just try it on some teenagers and you’ll see what I mean! You Are Worth Rest Keeping a spiritual practice reminds me of a lighthouse on the water. It might be freezing outside, and ships are sinking all around me, but in that lighthouse is a warm bed, a fire, a hot cup of tea and beautiful music playing. (Okay, so my lighthouse is more of an AirBnB but you get the idea!) Instead of focusing on the chaos on the stormy sea, I can stay in gratitude that I am cared for inside. Because God is my keeper, I don’t need to worry about the rent or people coming in to steal my stuff. That house is open 24 hours for me with a sign on the door, “Come on in, Andrea. You are loved. You are welcome.” There, in that lighthouse, I can lay down any expectations I have of myself and remember that I am a child of God and nothing else matters. And, from that place of rest and contentment, I can light a candle and look out my window. Sometimes I’ll see sun. But sometimes I’ll see other fellow travelers who are drowning in horrific waves. Having been there myself, I can understand their struggle. And then, best of all — and only because I will have had my time of rest — I can leave the safety of the lighthouse with a sense of purpose. I can get into my boat and, with a spirit stronger than the weather around me, motor out to help some of them. My purpose isn’t to do better, it’s to be better. As a perfectionist, I struggle with always wanting things done a certain way. But when I remember I don’t have to be perfect, because only God is, I can relax and let my true nature come out to play. I don’t need to check off one more box on an endless to do list. I simply need to sit still and, once again, be reminded who I really am… who my authentic nature is. Who is that nature? She is someone who likes to feed people. She has Taco Tuesday complete with mariachi hats… who is writing a musical about camels… who reads Roald Dahl to her homeroom every day and can’t pass up a yard sale or a stray dog. I love that Andrea, but the only way I can let her out to play and to “be” is to bring God in. And the only way to do that is to begin each day in prayer and meditation. My practice is my answer. And so, friends, if you already have a morning practice where you can connect to the God of your understanding, that’s awesome! If not, I encourage you to start. It’s not easy at first (that’s why they call it “practice”) but in time, like any routine, a pattern will establish. I can promise you that in nurturing your spirit, you will find you are more able to face whatever comes your way each day. And not only will your soul thank you, everyone around you will, too. Until tomorrow, Andrea About Me I’m a published TV, blog, magazine and book writer who also coaches moms and grandmoms to write books rooted in wisdom, spirituality and humor. Come back Monday — Friday where I’ll post about spirituality, writing and sobriety. And sometimes tacos. Because Tacos make everything better. Always. DON’T MISS A NEWSLETTER! You can sign up for my email list here where I’ll send you a newsletter all about book writing every Wednesday. Happy Hump Day indeed!

https://medium.com/the-innovation/want-peace-build-your-life-around-your-spiritual-practice-1dead875fcf

['Andrea R Frazer']

2020-11-07 15:06:32.425000+00:00

['Books', 'Writing', 'Faith', 'God', 'Meditation']

Favorite Developer Tools for 2021

In rounding out the year, I realized that I now spend at least 40% of my time in different tools than last year. This is both due to COVID where my teams are remote, but also due to tools maturing. 1. Visual Studio Code The new standard. A year ago, I would have said Sublime Text was my only goto code editor. VSCode now has basically all the features of Sublime Text and more. It is easily available on ARM Architecture compute (NVIDIA Jetson, Raspberry Pi, etc) which really helps for building embedded or robotic projects. There are clean and understandable interfaces and it also includes a lot of extensions such as SSH Code synchronization and other interesting plugins. Visual Studio Code has matured in the last few years. 2. Docker Dockerize your dev environment. It’s Amazing. In the past, I used to only use Docker as a container for deployment of scalable systems. I would first develop the code in my dev environment, then I would figure out how to make that code run in a Docker where I packaged it up and sent it off. Now I use it much like a system-wide like a virtual environment which lets me code in any OS type or version with any custom dependencies from my Mac or Ubuntu dev environment. One of the most valuable use cases has been in doing robotic development using ROS and ROS 2. The dependencies to get ROS going are significant and, for some reason still seem to be error prone and unstable. Therefore, starting from a docker image which is based on a stable build of ROS with the added apt-get install {package} commands for my specific install, and then mounting the code directory directly into the container means that I can code from within my core dev environment but execute it in the different OS. docker run -d -t --name robot_env --restart unless-stopped -v `pwd`:/root/workspace osrf/ros:foxy-desktop The above line of code will boot a container with ROS2 in it and the current directory mapped to /root/workspace , ready to go. The best part is that the time to deploy goes way down as you are running exactly as you would in production. 3. GITHub Still the goto. It is amazing how a single system for saving code can be so engrained in the consciousness of developers, but it is and it works. GITHub still holds the core of versioned code and has added additional features which enable teams to more efficiently use it as a central communication hub for development. 4. PostMan Saves hours accessing a new API. Whenever you jump in to integrate a new platform or service into your project, you have to dig through the swagger docs, try to figure out what authentication they use, sort our payload details, try to fix CORS issues and then write 10–100 lines of code to get a reply. Or, you just boot PostMan, type in the URL with the payload, set a few headers and are good to go. Then, a week later when you forgot what you wrote, it is all there in the history. Postman enables you to easily test new APIs without writing code and to write groups of queries and reuse them, saving significant time. 5. Ubuntu Linux It is a clean environment. Unless you are developing directly for MacOS or mobile, Ubuntu is a much cleaner and, many times, better environment to write code in. With Apt having clearer dependencies, significantly more Linux support on Stack Overflow in the last few years and full stack developers now using Ubuntu, rather than Windows or Mac, as their base, starting out and building a projects in ubuntu has become much easier. While Ubuntu has been around for a very long time, the groundswell of non-sys-admin users has really increased, making it a much better general-purpose dev environment for coding. 6. CircleCI Better deployment. CircleCI has advanced drastically with its updated scripting language, cross-architecture support and clean integrations with GITHub and other tools. I realized I had forgotten we were even using it for a while because everything just worked. Compared to Jenkins and many other CI/CD platforms, the overhead is significantly less, and it is not tied to a specific larger platform. Note: That said, I will probably check out GITHub Actions for 2021. CirceCI just works and is flexible enough with its container-based deployments that you can do anything with it that you want. 7. Chrome Dev Tools Debug the hardware innards of the browser. This last year, my teams released a lot of in-browser features where we had to optimize React.js code due to huge data sizes and also had to stabilize WebRTC video connections in adverse environments. All the other browsers had just a few simple tools for introspection or logging, but Chrome not only exposed much more and better data(chrome://webrtc-internals), it also formatted the logs and graphs cleanly where you could directly debug your issues in browser. No matter if it was CSS, Javascript or API CORS issues, I found that whenever my team needed to fix something, even if it was in a different browser, they would use Chrome first to understand it. Chrome has a huge number of debugging tools, including chrome://webrtc-internals, which give a fully detailed view into what is happening when something breaks. 8. Slack A repository of organized knowledge, in addition to messaging. I never thought I would put a messaging app in my list of tools which significantly increase development efficiency. In the last year, especially with Covid, Slack has become more necessary. I realized the biggest change is that we now use it for a group consciousness, where I find myself looking up pictures people upload, reviewing code snippets and starting zoom and hangouts meetings from inside Slack itself. With the addition of groups for channels and other subtle things, it has become a lot more efficient. We even run our daily standup in it using Standuply. Slack has become a repository of knowledge, images, videos and code snippets, not just a messaging service. 9. Google Meet We have had a lot of time to play with and optimize video conferencing in 2020. For external meetings, we use Zoom, but I have found that for shared debugging sessions, our team uses hangouts. I think the simplest reason is that anyone can start it from the browser. They don’t need to have a zoom account, log in, then set up a new meeting. The screen sharing, and addition of hidden backgrounds, has really helped make it a tool we can use in the background while working together.

https://hansclee.medium.com/favorite-developer-tools-of-2020-736ea5a9dd4b

['Hans Lee']

2020-12-10 17:12:59.210000+00:00

['Productivity', 'Development', 'Programming', 'DevOps']

This Is How I Get The Most Out Of A Headline Analyser Tool.

Top Headline # 1 — This Is the Best Way To Think About … Analyser Score: 85 points. This is one headline type that points to the highest utility of thinking. There are many ways to skin a cat. And this is the best way. You help readers save their time by presenting the best way ahead. It could be a short-cut or a life trivia. In short, this is the way ahead. Top Headline # 2 — This Is How I Got The Most Out Of … Analyser Score: 82 points. This shows the reader that you are an experimental scientist, and you found a way to extract the most value out of an activity. This is about extracting and retaining the most information from a book, for instance. It is highly valued by students who are coping with their examinations. Top Headline # 3 — How To … And Get The Most Out Of … When You Have No Time … Analyser Score: 87 points. As with the Top 2, this category is about showing the short-cut with a time dimension. What if all we have is 10 minutes? What is the best way to get the most out of a gym workout over a 30-minute lunch break? People who struggle with time control will be attracted to such headlines. Top Headline # 4 — How To Be … All The Time … Analyser Score: 84 points. This headline is about life lessons, in my opinion. Try inserting different words in between “To Be” and “All The Time.”. You will realize that positive words make sense. Negative words do not. Take, for instance, “How To Be Calm All The Time.”. It showcases life lessons accumulated over time. Many people need it. I need it. Thanks for writing it. Top Headline # 5 — What You Can Do When You Are Sick And Tired Of … Analyser Score: 84 points. This headline deals with overcoming negativity. I think it deserves a pre-set high score because we are all sick and tired of something. I am sick and tired of people trying to tell me what to do or what not to do. I am sick and tired of listening to people telling me how to do things this way or that when they are not doing it. You know, things like that. Top Headline # 6 — What You Need To Know About … And How To Deal With it … Analyser Score: 85 points. This headline type deals with circumstances. Insert in a difficult circumstance you have encountered, and you will know what I know. They can range from asking for a pay raise, emotional people, tendering a resignation. It teaches readers to expect and how to deal with the next step. Top Headline # 7 — What Happens When You Start Doing … For The First Time … Analyser Score: 86 points. This is about personal growth. It shows how uncomfortable we are attempting to do things for the first time. It also shows how it really isn’t that difficult or how it is tough beyond comprehension. In any case, this is about a reflection.

https://medium.com/technology-hits/this-is-how-i-get-the-most-out-of-a-headline-analyser-tool-bb0365a8ead0

['Aldric Chen']

2020-12-26 12:51:45.031000+00:00

['Writing Tips', 'Technology', 'Productivity', 'Communication', 'Writing']