Mathematical Matrix Methods lie at the root of most methods of machine learning and data analysis of tabular data. Learn the basics of Matrix Methods, including matrix-matrix multiplication, solving linear equations, orthogonality, and best least squares approximation. Discover the Singular Value Decomposition that plays a fundamental role in dimensionality reduction, Principal Component Analysis, and noise reduction. Optional examples using Python are used to illustrate the concepts and allow the learner to experiment with the algorithms....

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創建者 Valerii M

•Jan 23, 2020

Good set of sections and examples, important topics are considered. Peculiar lecture style (unusual for Coursera), but it's ok. It would be a good idea to add a videos to the last module.

I think it was a good practice. Thanks!

創建者 Denis B

•Nov 18, 2019

Pros and cons.

Sometimes it's hard to find in this course needed information to solve Assignments.

But you have to dig deeper from outside sources.

創建者 Ankit G

•Jan 27, 2020

All readings are well chosen , and actually helped me understand.

The video quality needs to be improved. Better explanations to some sections could help along with explanantions to why answers were right or wrong in Assignments

創建者 Paul O

•Jan 12, 2020

I subscribe to Coursera so I can take as many courses as I like for a monthly fee. There are a lot of excellent courses on Coursera but this isn't one of them. I would be really angry if I had paid specifically for this course. There are issues with the practice quizzes that were pointed out in the discussion forum months ago for which there is still no reply. Staff should at least glance at the forum to see if there are any problems with the course material. The lectures cover the simple ideas, but the harder material is outsourced mostly to http://mathonline.wikidot.com/ and sundry pdf documents. Some of the reading material is a lot more advanced than the course itself.