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Matrix Factorization and Advanced Techniques(으)로 돌아가기

미네소타 대학교의 Matrix Factorization and Advanced Techniques 학습자 리뷰 및 피드백

4.3
별점
181개의 평가

강좌 소개

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....

최상위 리뷰

HL

2021년 1월 2일

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

2017년 7월 18일

great courses! They invite a lot of interviews to let me understand the sea of recommend system!

필터링 기준:

Matrix Factorization and Advanced Techniques의 26개 리뷰 중 26~26

교육 기관: PRATIK K C

2020년 6월 9일

Could have been better