Feature scaling stands for normalizing variable values into a certain range.
Matrix factorization is a class of algorithms used for recommender systems in machine learning. Matrix factorization algorithms work by decomposing dimensionality. Commonly known matrix factorization algorithms are SVD and PCA.
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