Retour à Matrix Factorization and Advanced Techniques
Avis et commentaires pour d'étudiants pour Matrix Factorization and Advanced Techniques par Université du Minnesota
181 évaluations
À propos du cours
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.
Meilleurs avis
HL
2 janv. 2021
Really enjoyed the course!
One suggestion I have is to blend in even more advanced techniques such as using neural networks (e.g. NCF)
LL
18 juil. 2017
great courses! They invite a lot of interviews to let me understand the sea of recommend system!
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26 - 26 sur 26 Avis pour Matrix Factorization and Advanced Techniques
par PRATIK K C
•9 juin 2020
Could have been better
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