Matrix Factorization and Advanced Techniques

Coursera MOOC / Non-credit USD 79

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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.

What you'll learn

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

Skills you'll gain

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

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