Recommender Systems: An Applied Approach using Deep Learning - Neural Collaborative Filtering

The video tutorial explains neutral collaborative filtering, a deep learning method for recommendations. It covers embedding layers, user and item latent vectors, and how these are paired and fed into a network. The process involves factorization and the use of a multilayer perceptron (MLP) to determine if an item should be recommended to a user. The tutorial also touches on scoring and the decision-making process for recommendations. Finally, it introduces another collaborative filtering method using auto encoders.

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