About the content
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.
Michael D. Ekstrand
Dept. of Computer Science, Boise State University
Joseph A Konstan
Distinguished McKnight Professor and Distinguished University Teaching Professor
Computer Science and Engineering
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