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Matrix factorization using alternating least squares for movie recommendation

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Movie recommendation algorithm implemented in Julia

Matrix factorization using alternating least squares for movie recommendation

The file recommend.jl contains a single run of the ALS algorithm with no cross-validation or parameter tuning.

The file recommend_full.jl contains the ALS algorithm with 10-fold cross-validation and considers ranges for three parameters: the number of features, the learning rate, and the maximum number of iterations of the algorithm.

Both files use the ratings.dat file from the 1M dataset from http://grouplens.org/datasets/movielens/

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