Matrix Factorization and Advanced Techniques

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Free Online Course: Matrix Factorization and Advanced Techniques provided by Coursera is a comprehensive online course, which lasts for 6 weeks long, 16 hours worth of material. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from Coursera. Matrix Factorization and Advanced Techniques is taught by Michael D. Ekstrand and Joseph A Konstan.

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