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.
About this Course
- 5 stars53.26%
- 4 stars33.15%
- 3 stars8.15%
- 2 stars4.34%
- 1 star1.08%
TOP REVIEWS FROM MATRIX FACTORIZATION AND ADVANCED TECHNIQUES
Very good. Per closing comments, it probably needs an update (since 2016) as this is active, progressive area.
Interview with Francesco Ricci
is very knowledgeable about context aware Recommender System.
Awesome course especially for those doing Ph.D in recommender systems
Really enjoyed the course!
One suggestion I have is to blend in even more advanced techniques such as using neural networks (e.g. NCF)
About the Recommender Systems Specialization
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