Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Online Course

Matrix Factorization and Advanced Techniques

University of Minnesota via Coursera

86
  • Provider Coursera
  • Cost Free Online Course (Audit)
  • Session In progress
  • Language English
  • Certificate Paid Certificate Available
  • Duration 6 weeks long
  • Learn more about MOOCs

Taken this course? Share your experience with other students. Write review

Overview

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.

Syllabus

Preface

Matrix Factorization (Part 1)
-This is a two-part, two-week module on matrix factorization recommender techniques. It includes an assignment and quiz (both due in the second week), and an honors assignment (also due in the second week). Please pace yourself carefully -- it will be difficult to finish in two weeks unless you start the assignments during the first week.

Matrix Factorization (Part 2)

Hybrid Recommenders
-This is a three-part, two-week module on hybrid and machine learning recommendaton algorithms and advanced recommender techniques. It includes a quiz (due in the second week), and an honors assignment (also due in the second week). Please pace yourself carefully -- it will be difficult to finish the honors track in two weeks unless you start the assignments during the first week.

Advanced Machine Learning

Advanced Topics

Taught by

Michael D. Ekstrand and Joseph A Konstan

Help Center

Most commonly asked questions about Coursera

Reviews for Coursera's Matrix Factorization and Advanced Techniques Based on 0 reviews

  • 5 star 0%
  • 4 star 0%
  • 3 star 0%
  • 2 star 0%
  • 1 star 0%

Did you take this course? Share your experience with other students.

Write a review

Class Central

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free

Never stop learning Never Stop Learning!

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free