Systems based on collaborative filtering are the workhorse of recommender systems. They yield great results when abundant data is available. Unfortunately, their performance suffers when encountering new items or new users.

In this talk, I'm going to talk about hybrid approaches that alleviate this problem, and introduce a mature, high-performance Python recommender package called LightFM.