readme: ---
  library_name: keras
  tags:
  - collaborative-filtering
  - recommender
  - tabular-classification
  license:
  - cc0-1.0
  ---
  
  ## 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>