Understand matrix factorization as a way to come up with user attributes.
- [Instructor] Because the ratings matrix is equal…to the result of multiplying the user attributes matrix…by the movie attributes matrix,…we can work backwards using matrix factorization…to find values for U and M.…In code, we use an algorithm called,…low rank matrix factorization, to do this.…Let's look at how this algorithm works.…Matrix factorization is the idea that a large matrix…can be broken down into smaller matrices.…So, assuming that we have a large matrix of numbers,…and assuming that we want to be able…to find two smaller matrices that multiply together…to result in that large matrix,…our goal is to find two smaller matrices…that satisfy that requirement.…
If you happen to be an expert in linear algebra,…you might know that there are standard ways…to factor a matrix,…such as using a process called,…singular value decomposition.…But this is a special case where that won't work.…The problem is that we only know some of the values…in the large matrix.…Many of the entries in the large matrix are blank,…
Author
Released
4/10/2017Recommendation systems are a key part of almost every modern consumer website. The systems help drive customer interaction and sales by helping customers discover products and services they might not ever find themselves. The course uses the free, open source tools Python 3.5, pandas, and numpy. By the end of the course, you'll be equipped to use machine learning yourself to solve recommendation problems. What you learn can then be directly applied to your own projects.
- Building a machine learning system
- Training a machine learning system
- Refining the accuracy of the machine learning system
- Evaluating the recommendations received
Skill Level Intermediate
Duration
Views
Related Courses
-
Introduction
-
Welcome1m 1s
-
Set up environment2m 15s
-
-
1. The Basics of Making Recommendations
-
2. Ways of Making Recommendations
-
3. Getting to Know Our Tools
-
4. Building the Framework for Our Recommendation System
-
5. Collaborative Filtering with Matrix Factorization
-
6. Testing Our System
-
Use regularization1m 52s
-
7. Using the Recommendation System in a Real World Program
-
Find similar products1m 59s
-
Conclusion
-
Wrap up47s
-
- Mark as unwatched
- Mark all as unwatched
Are you sure you want to mark all the videos in this course as unwatched?
This will not affect your course history, your reports, or your certificates of completion for this course.
CancelTake notes with your new membership!
Type in the entry box, then click Enter to save your note.
1:30Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.
Share this video
Embed this video
Video: How matrix factorization works