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README.md

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----
-license: mit
----
+---
+library_name: tf-keras
+license:
+- cc0-1.0
+tags:
+- collaborative-filtering
+- recommender
+- tabular-classification
+---
+
+## Model description
+
+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/). 
+
+Full credits to [Siddhartha Banerjee](https://twitter.com/sidd2006).
+
+## Intended uses & limitations
+
+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.
+
+## Training and evaluation data
+
+The dataset consists of user's ratings on specific movies. It also consists of the movie's specific genres.
+
+## Training procedure
+
+The model was trained for 5 epochs with a batch size of 64.
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- optimizer: {'name': 'Adam', 'learning_rate': 0.001, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
+- training_precision: float32
+
+ ## Training Metrics
+
+| Epochs | Train Loss | Validation Loss |
+ |--- |--- |--- |
+| 1| 0.637|  0.619| 
+| 2| 0.614|  0.616| 
+| 3| 0.609|  0.611| 
+| 4| 0.608|  0.61| 
+| 5| 0.608|  0.609| 
+ ## Model Plot
+
+<details>
+<summary>View Model Plot</summary>
+
+![Model Image](./model.png)
+
+</details>

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history.json

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+    0.6080355644226074,
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