AI-Accelerated Product Development
Matrix Factorization for Recommender Systems
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This list will go over three matrix factorization methods (unconstrained, SVD, and NMF) used in Recommender Systems.
Potential Use Cases
Recommending movies (Netflix), "watch next" (YouTube), or "items you might like" (Amazon).
Who is This For ?
Click on each of the following
to see details.
1. Introduction to Matrix Factorization
Overview of the use of matrix factorization applied to Netflix recommendation
2. Lecture Notes on Unconstrained Matrix Factorization Methods from Carnegie Mellon
What is the theory behind unconstrained matrix factorization?
3. SVD for Recommender Systems
How to implement SVD for recommender systems?
4. Video Lecture on SVD for Recommender Systems from Stanford
What is the theory behind SVD for recommender systems?
5. Lecture Notes on Non-negative Matrix Factorization from Stanford
What is the theory behind non-negative matrix factorization?
6. Python Package (NIMFA) to solve NMF
How do I solve NMF and other factorization problems in Python