Matrix Factorization and Advanced Techniques
In this course you will learn a variety of matrix factorization and hybrid machine learning techniques for recommender systems. Starting with basic matrix...
By Michael D. Ekstrand on Coursera
About This Course
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.
Frequently Asked Questions
How much does Matrix Factorization and Advanced Techniques cost?
Visit the Matrix Factorization and Advanced Techniques course page for current pricing and available discounts.
Who teaches Matrix Factorization and Advanced Techniques?
Matrix Factorization and Advanced Techniques is taught by Michael D. Ekstrand, University of Minnesota.
What skill level is Matrix Factorization and Advanced Techniques for?
This course is designed for advanced learners.
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