Created
January 7, 2021 22:43
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Sample code for my Medium article "How to build powerful deep recommender systems using Spotlight".
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| """ | |
| Utility functions for generating movie recommendations using matrix factorization models | |
| """ | |
| def get_metadata(movie_id, metadata): | |
| """ | |
| Retrieves the metadata for a movie given the movie ID | |
| """ | |
| movie_data = metadata[metadata['movieId'] == movie_id] | |
| return movie_data[['original_title', 'release_date', 'genres']].to_dict(orient='records') | |
| def recommend_movies(user_id, metadata, model, n_movies=5): | |
| """ | |
| Recommends movies for user using a matrix factorization model. | |
| """ | |
| pred = model.predict(user_ids=user_id) | |
| indices = np.argpartition(pred, -n_movies)[-n_movies:] | |
| best_movie_ids = indices[np.argsort(pred[indices])] | |
| return [get_metadata(movie_id + 1, metadata) for movie_id in best_movie_ids] |
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