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README.md
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---
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library_name: keras
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tags:
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- collaborative-filtering
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- recommender
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- structured-data-classification
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license:
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- cc0-1.0
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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>
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