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In the IBM Watson Studio, there is a large collaborative community ecosystem of articles, datasets, notebooks, and other A.I. and ML. assets. Users of the system interact with all of this. This is a recommendation system project to enhance the user experience and connect them with assets. This personalizes the experience for each user.
This Jupyter Notebook outlines my process as I create a movie recommendation system using matrix factorization. I use the public 100k MovieLens dataset.
This repo contains the implementation of netflix's original recommender system based on matrix factorization which changed the recommender systems forever 10 years back. Delve in to the notebooks to learn the intricacies of the magic box that knows your exact taste.