Building A Collaborative Filtering Recommender System with TensorFlow

Therefore, collaborative filtering is not a suitable model to deal with cold start problem, in which it cannot draw any inference for users or items about which it has not yet gathered sufficient information. But once you have relative large user -- item interaction data, then collaborative filtering is the most widely used recommendation approach. And we are going to learn how to build a collaborative filtering recommender system using TensorFlow. We are again using booking crossing dataset that can be found here. So, our final dataset contains 3,192 users for 5,850 books.