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Matrix Factorization and Advanced Techniques

Matrix Factorization and Advanced Techniques

This course is part of Recommender Systems Specialization

Instructors: Michael D. Ekstrand

15,995 already enrolled

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6 modules

Gain insight into a topic and learn the fundamentals.

190 reviews

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

6 modules

Gain insight into a topic and learn the fundamentals.

190 reviews

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

7 assignments

Taught in English

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This course is part of the Recommender Systems Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 6 modules in 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.

Module details

What's included

1 video

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.

What's included

5 videos1 reading

What's included

2 videos2 readings5 assignments1 programming assignment

2 videosTotal 15 minutes

Assignment Introduction8 minutes
Programming Matrix Factorization7 minutes

2 readingsTotal 20 minutes

Assignment Instructions10 minutes
Intro - Programming Matrix Factorization10 minutes

5 assignmentsTotal 68 minutes

Matrix Factorization Assignment Part l10 minutes
Matrix Factorization Assignment Part ll10 minutes
Matrix Factorization Assignment Part lll10 minutes
Matrix Factorization Quiz8 minutes
SVD Programming Eval Quiz30 minutes

1 programming assignmentTotal 180 minutes

Programming SVD180 minutes

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.

What's included

6 videos

What's included

3 videos

What's included

7 videos1 reading2 assignments1 programming assignment

7 videosTotal 133 minutes

Context-Aware Recommendation I : Interview with Francesco Ricci21 minutes
Context-Aware Recommendation II: Interview with Bamshad Mobasher (Part 1)22 minutes
Context-Aware Recommendation II: Interview with Bamshad Mobasher (Part 2)18 minutes
Industry Practical Issues: Inteview with Anmol Bhasin27 minutes
Recommending Music - Interview with Paul Lamere14 minutes
Specialization Wrap Up22 minutes
Programming Hybrids & Learning to Rank9 minutes