Matrix Factorization and Advanced Techniques

University of Minnesota
via Coursera
Save (0)
ClosePlease login

No account yet? Register

In this course you will learn a variety of matrix factorization and hybrid machine learning techniques for recommender systems. Starting with basic matrix factorization, you will understand both the intuition and the practical details of building recommender systems based on reducing the dimensionality of the user-product preference space. Then you will learn about techniques that combine the strengths of different algorithms into powerful hybrid recommenders.

Instructor(s)

Michael D. Ekstrand, Joseph A Konstan
University of Minnesota
via Coursera
Free (audit)
English
Paid Certificate Available
Approx. 16 hours to complete
Self paced
Subtitles: Subtitles: French, Portuguese (European), Russian, English, Spanish