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.
- 5 stars53.26%
- 4 stars33.15%
- 3 stars8.15%
- 2 stars4.34%
- 1 star1.08%
來自MATRIX FACTORIZATION AND ADVANCED TECHNIQUES的熱門評論
great courses! They invite a lot of interviews to let me understand the sea of recommend system!
Very good. Per closing comments, it probably needs an update (since 2016) as this is active, progressive area.
The content is really good, but overall the interviews with experts in the field are the best of this course.
Programming Assignments are not clear enough and the quiz for the last one seems to be a bit off.