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Comparison of recommender algorithms using the BookCrossing data set

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Book Recommender System Model Comparison

Tyler Kinkade

The ability to quickly and effectively make recommendations to customers can increase profits in the online shopping industry and boost customer retention in the entertainment streaming industry by helping customers efficiently navigate the overwhelming number of options to locate the most relevant choices. In this project, I compare six models used for recommending items to users.

See the project.ipynb Jupyter notebook for the full report.

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Comparison of recommender algorithms using the BookCrossing data set

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