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Set of music recommendation algorithms we implemented to join the annual RecSys Competition at Politecnico di Milano in 2017.

Python 8.67% HTML 6.24% CMake 0.01% C++ 0.09% Jupyter Notebook 82.09% Rich Text Format 2.90%
recommender-system slim bpr matrix-factorization funk-svd hybrid-recommender-system challenge kaggle bayesian-optimization genetic-algorithm

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