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Large-scale Matrix Factorization Recommender System Algorithm

The Alternating Least Squares (ALS) algorithm is applied to given user-item ratings to predict the ratings of unrated items.

The training set consists of 20 million ratings. The testing set is made up of 1.4 million user-item pairs.

The MAE acquired on the testing set is 0.6537.

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Alternating Least Squares (ALS) recommender system

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