Online Course
Matrix Factorization and Advanced Techniques
University of Minnesota via Coursera
Found in
Artificial Intelligence Courses
9 Months, Online Machine Learning & AI Diploma
Columbia Engineering Executive Education
via EMERITUS
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- Provider Coursera
- Cost Free Online Course (Audit)
- Session Upcoming
- Language English
- Certificate Paid Certificate Available
- Duration 6 weeks long
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Overview
Class Central Tips
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.
Syllabus
Preface
Matrix Factorization (Part 1)
-This is a two-part, two-week module on matrix factorization recommender techniques. It includes an assignment and quiz (both due in the second week), and an honors assignment (also due in the second week). Please pace yourself carefully -- it will be difficult to finish in two weeks unless you start the assignments during the first week.
Matrix Factorization (Part 2)
Hybrid Recommenders
-This is a three-part, two-week module on hybrid and machine learning recommendaton algorithms and advanced recommender techniques. It includes a quiz (due in the second week), and an honors assignment (also due in the second week). Please pace yourself carefully -- it will be difficult to finish the honors track in two weeks unless you start the assignments during the first week.
Advanced Machine Learning
Advanced Topics
Matrix Factorization (Part 1)
-This is a two-part, two-week module on matrix factorization recommender techniques. It includes an assignment and quiz (both due in the second week), and an honors assignment (also due in the second week). Please pace yourself carefully -- it will be difficult to finish in two weeks unless you start the assignments during the first week.
Matrix Factorization (Part 2)
Hybrid Recommenders
-This is a three-part, two-week module on hybrid and machine learning recommendaton algorithms and advanced recommender techniques. It includes a quiz (due in the second week), and an honors assignment (also due in the second week). Please pace yourself carefully -- it will be difficult to finish the honors track in two weeks unless you start the assignments during the first week.
Advanced Machine Learning
Advanced Topics
Taught by
Michael D. Ekstrand and Joseph A Konstan
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