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Recommendations to users by applying knowledge-based, collaborative filtering, content-based and matrix factorization recommendations

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yanhan-si/Recommender-System

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Recommendations with IBM

In this project, we analyzed the interaction that users have with articles and built a recommender system to users using real data from the IBM Watson Studio platform.

Types of recommendations implemented in this project:

  • Knowledge Based Recommendations

  • Collaborative Filtering Based Recommendations

  • Content Based Recommendations

  • Matrix Factorization

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Recommendations to users by applying knowledge-based, collaborative filtering, content-based and matrix factorization recommendations

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