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.
Informações sobre o curso
- 5 stars53,26%
- 4 stars33,15%
- 3 stars8,15%
- 2 stars4,34%
- 1 star1,08%
Principais avaliações do MATRIX FACTORIZATION AND ADVANCED TECHNIQUES
The content is really good, but overall the interviews with experts in the field are the best of this course.
Really enjoyed the course!
One suggestion I have is to blend in even more advanced techniques such as using neural networks (e.g. NCF)
Interview with Francesco Ricci
is very knowledgeable about context aware Recommender System.
Programming Assignments are not clear enough and the quiz for the last one seems to be a bit off.
Sobre Programa de cursos integrados Sistemas de recomendação
Perguntas Frequentes – FAQ
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