Stock Price Prediction App

Welcome to the Stock Price Prediction App! This app allows you to visualize stock price data, explore technical indicators, and make short-term price predictions using machine learning models.

Created and designed by Vikas Sharma.

Description
Features
Setup
Usage
Technologies
License

Description

The Stock Price Prediction App is a Streamlit-based web application that provides users with tools to analyze historical stock price data, visualize technical indicators, and make short-term price predictions using different machine learning models.

Features

Visualize Technical Indicators: Explore various technical indicators such as Bollinger Bands, MACD, RSI, SMA, and EMA to gain insights into stock price trends.
Recent Data Display: View the most recent data of the selected stock, including the last 10 data points.
Price Prediction: Predict future stock prices using machine learning models including Linear Regression, Random Forest Regressor, Extra Trees Regressor, KNeighbors Regressor, and XGBoost Regressor.

Setup

Clone the repository:

git clone https://github.com/vikasharma005/Stock-Price-Prediction.git

Navigate to the project directory:
```
cd stock-price-prediction-app
```
Install the required Python packages using pip:
```
pip install -r requirements.txt
```

Usage

Run the Streamlit app:
```
streamlit run app.py
```
The app will open in your default web browser. Use the sidebar to choose options for visualization, recent data display, or making price predictions.
Follow the on-screen instructions to input the stock symbol, select a date range, and choose technical indicators or prediction models.