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can anyone explain difference between Alternating Least Squares(ALS) and the recommendation systems?

it will be helpful if you give me an example.

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Recommendation systems eg. Netflix movie recommendations, I assume its pretty straight forward to get. Recommendations systems can be in either of content based filtering, collaborative filtering and combination of these two.

Now, we can use matrix factorization for solve this learning problem (problem here is the recommending movies). cut short, it turns out to be an optimization problem and there are method available such as gradient decent (slow and costly in this case) and another is ALS algorithm.

So, ALS is an algorithm which you can use to solve the learning problem a.k.a build recommendation systems.

Please read here more-

http://stanford.edu/~rezab/classes/cme323/S15/notes/lec14.pdf

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