Recommender tutorials¶
Harvard’s CS50¶
CS50 is Harvard University’s introduction to computer science and the art of programming. They provide an easy to follow introduction to recommender systems:
Google’s course¶
Google designed an excellent course to expand your knowledge of recommendation systems where they explain different models used in recommendation, including matrix factorization and deep neural networks:
Some of the covered concepts and examples are also explained in this video series:
Recommendation systems overview:
Content-based filtering & collaborative filtering:
Andrew Ng¶
In this video series, Andrew Ng introduces recommender algorithms such as the collaborative filtering algorithm and low-rank matrix factorization (video created by Stanford University for the course “Machine Learning”):