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I'm fairly new to ML/AI, i'm trying learn the content based recommendation - here is my source code - https://github.com/jaganlal/content-based-recommender

I'm using MovieLens 20M dataset - tags.csv to recommend similar movies based on its tag. But whenever i run

cosine_similarities = linear_kernel(tfidf_matrix, tfidf_matrix)

The python cell keeps executing and doesn't return at all. The code can be found at https://github.com/jaganlal/content-based-recommender

Am I doing anything wrong? Any help is highly appreciated.

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    $\begingroup$ Try to use part of dataset, may be first 1000 of rows. Try to limit max_features in TfidfVectorizer to 10 or so. Try use dense_output=False for linear_kernel. Then it will work try to increase something. I think it's taking too long to compute such things for full dataset. $\endgroup$ – CrazyElf Feb 4 at 13:04

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