Matrix Methods(으)로 돌아가기

# 미네소타 대학교의 Matrix Methods 학습자 리뷰 및 피드백

4.2
별점
133개의 평가
38개의 리뷰

## 강좌 소개

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....

## 최상위 리뷰

TT

May 18, 2020

This Course content is very good and has good real-time examples. However, the Instructor should add a few videos on SVD, Maximum dilation, and Shrinkage and Direction of Maximum Dilation.

MP

Aug 17, 2020

Thank you so much for giving me this opportunity to learn about matrix methods. This is helpful for my career and it is useful to all the beginners.

필터링 기준:

## Matrix Methods의 37개 리뷰 중 26~37

교육 기관: Ntiamoah K

Jun 05, 2020

Very good intuition into Matrix applications

교육 기관: Ankit G

Feb 11, 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

교육 기관: Mandar N

Jul 09, 2020

Great examples and a lot of reading material. More videos on SVD would have helped

교육 기관: DUNDI J T

Apr 29, 2020

i feel there should be solved examples for learners,,

교육 기관: Yung-Chuan C

Apr 29, 2020

The python content in this course is almost zero. The only thing I learn useful is the section about "singualr value decomposition" (the only reason why I still give it a 2-star review). However there's no lecture about the topic but two papers to read through. The instructor only contributes to easy matrix stuff in first three weeks and convinently skip the harder content in week 5. The video is not instructive enough. Compare to other courses from Coursera, this course is poor in quality and preparation.

교육 기관: Byron H D

Mar 02, 2020

I did learn some things, so I hate to review the course harshly, but there were numerous errors in the quizzes which have been there for a long time (based on forum comments) and have not been addressed. If completely redone and troubleshot the course has potential but as it stands it really isn't up to Coursera standards.

교육 기관: Raffaello Z

Apr 23, 2020

the course topics are interesting, unfortunately a video on week 5 would have been very important.

there are several errors in the test which made completing the test unnecessary difficult.

교육 기관: Axel A R Q

Jul 02, 2020

Falta mayor explicación y ejemplos

교육 기관: sri p b r

Sep 05, 2020

Excellent

교육 기관: 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.

교육 기관: Ksenia E

Apr 13, 2020

This course is really bad. There are a lot of mistakes in reading material and exercises. Videos are poor and not clear. Teaching stuff doesn't respond. The first two weeks were fine, but others are not. The last week doesn't have any videos at all. The reading material is from different sites and books and has no structure.

교육 기관: Julian A C

Sep 14, 2020

Lecture and reading materials and very brief and don't cover all the topics on the assignments & quizzes. There are no lectures on SVD.