A Gentle Introduction to Matrix Factorization for Recommendations

Miguel González-Fierro
Nov. 28, 2021

Matrix Factorization is one of the most widely used methods in Recommendation Systems, whose ultimate goal is to understand what is the user preference for a set of items. For example, Netflix tries to understand what movie you would like to watch next. In this post, we explain in simple terms how Matrix Factorization works.


recommendation systems; matrix factorization; als

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