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user-collaborative-filtering

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Lodz97 / RecSys-PoliMi-2020

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The objective of the competition was to create the best recommender system for a book recommendation service by providing 10 recommended books to each user. The evaluation metric was MAP@10.

slim matrix-factorization recommender-systems bayesian-optimization polimi elasticnet user-collaborative-filtering item-collaborative-filtering content-based-recommendation alternating-least-squares hybrid-recommender-system implicit-feedbacks p3alpha
  • Updated Nov 19, 2021
  • Python

anudeepvanjavakam1 / Recommendations_with_IBM

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In the IBM Watson Studio, there is a large collaborative community ecosystem of articles, datasets, notebooks, and other A.I. and ML. assets. Users of the system interact with all of this. This is a recommendation system project to enhance the user experience and connect them with assets. This personalizes the experience for each user.

notebook python3 matrix-factorization recommendation-system recommendation-engine ibm-watson user-collaborative-filtering rank-based-recommendation user-engagement-and-retention
  • Updated Mar 26, 2023
  • HTML

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