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--- |
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library_name: tf-keras |
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license: |
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- cc0-1.0 |
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tags: |
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- collaborative-filtering |
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- recommender |
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- tabular-classification |
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--- |
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## Model description |
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This repo contains the model and the notebook on [how to build and train a Keras model for Collaborative Filtering for Movie Recommendations](https://keras.io/examples/structured_data/collaborative_filtering_movielens/). |
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Full credits to [Siddhartha Banerjee](https://twitter.com/sidd2006). |
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## Intended uses & limitations |
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Based on a user and movies they have rated highly in the past, this model outputs the predicted rating a user would give to a movie they haven't seen yet (between 0-1). This information can be used to find out the top recommended movies for this user. |
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## Training and evaluation data |
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The dataset consists of user's ratings on specific movies. It also consists of the movie's specific genres. |
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## Training procedure |
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The model was trained for 5 epochs with a batch size of 64. |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- optimizer: {'name': 'Adam', 'learning_rate': 0.001, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} |
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- training_precision: float32 |
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## Training Metrics |
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| Epochs | Train Loss | Validation Loss | |
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|--- |--- |--- | |
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| 1| 0.637| 0.619| |
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| 2| 0.614| 0.616| |
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| 3| 0.609| 0.611| |
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| 4| 0.608| 0.61| |
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| 5| 0.608| 0.609| |
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## Model Plot |
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<details> |
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<summary>View Model Plot</summary> |
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</details> |
