Coursera MOOC / Non-credit 0

Matrix Factorization and Advanced Techniques

Name: Matrix Factorization and Advanced Techniques
Price: 79 USD
Availability: InStock

University of Minnesota

About this course

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.

75/100

CourseAsk score

What the provider tells you: 24/45
Who stands behind it: 35/35
How complete the listing is: 16/20

Scores how much the provider publishes and who stands behind it — not how well it is taught.

What you'll learn

understand matrix factorization concepts
build recommender systems
implement hybrid machine learning techniques

Machine Learning #machine learning #dimensionality reduction #data analysis #recommender systems #collaborative filtering #matrix factorization #hybrid algorithms #user-product preferences

$79.00

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