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hybrid-approach

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TMDB_5000_Movie_recommendation_system is a repository for a hybrid movie recommendation system. Discover personalized movie recommendations based on user preferences and movie features using the TMDB 5000 Movies dataset.

  • Updated Apr 20, 2023
  • Jupyter Notebook

A personalized anime recommendation system developed using Python, incorporating both collaborative and content-based approaches. The system utilizes user ratings and anime metadata to provide hybrid recommendations, achieving a RMSE of 0.289, MAE of 0.213, and MSE of 0.084 on the test set.

  • Updated Dec 26, 2022
  • Jupyter Notebook

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