IvanJericevich/Recommender-Systems

Recommender systems are software tools and techniques that provide suggestions for items to be of use to a user. The collaborative filtering approach evaluates items using the opinions or ratings of other users. Alternatively, the content-based approach works by learning the items’ features to match the user’s preferences and interests. The code found in this repository implements several collaborative filtering and content-based methods: K-nearest neighbours, hierarchical clustering, association rule mining, ordinal logistic regression, classification trees, TF-IDF, and matrix factorisation.

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