From the course: Building Recommender Systems with Machine Learning and AI

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Restricted Boltzmann machines (RBMs)

Restricted Boltzmann machines (RBMs)

and recommender systems is the Restricted Boltzmann Machine or RBM for short. It's been in use since 2007, long before AI had its big resurgence, but it's still a commonly cited paper and a technique that's still in use today. Going back to the Netflix prize, the main things Netflix learned was as measured by RMSE and their scores were almost identical. Again, this shouldn't surprise us too much, since you know that you can model matrix factorization as a neural network, but they found that by combining matrix factorization with RBM's, the two of them working together provided even better results. They went from an RMSE of 8.9 to 8.8. A few years ago, Netflix confirmed they were still using RBM's as part of their recommender system that's in production. Let's learn how it works. First of all, if you're serious about using RBM's for recommendations, I recommend tracking down this paper so you can study it later once you understand the general concepts. It's from a team from the…

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