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Bewertung und Feedback des Lernenden für Matrix Methods von University of Minnesota

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210 Bewertungen

Über den Kurs

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....

Top-Bewertungen

TT

17. Mai 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

16. Aug. 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.

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26 - 50 von 55 Bewertungen für Matrix Methods

von Siva k T

15. Juni 2020

Excellent

von Dr K J

18. Juni 2020

nothing

von roshni s

6. Juni 2020

Good

von Jim L

8. Okt. 2021

I came from a statistics background and had little experience explicitly interpreting Matrix Algebra as vectors more from the viewpoint of physics. It was an excellent review for me and I buzzed through it in a few days. After retiring I walked away from math, but the course made me remember why I went down that road. I recommend this class.

von Denis B

18. Nov. 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.

von Muhammad S

20. Mai 2020

there was less suitable material for this course

von Kofi N K

5. Juni 2020

Very good intuition into Matrix applications

von Agrover112

10. Feb. 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

von Rituraj N

3. Jan. 2022

The lectures could be more engaging and more topics could certainly be covered. This course on matrix is too sparse!! Also, strangely, there were no lectures for the final week - only links were provided for reading materials.

von Mitzilin Z T C

24. März 2021

The topics of the course are good, nevertheless, the videos need explain all the topics in detail because, sometimes is hard to understand just reading the pdf materials.

von Mandar N

9. Juli 2020

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

von DUNDI J T

29. Apr. 2020

i feel there should be solved examples for learners,,

von Carlos F

16. Nov. 2021

I found the course very unbalanced and without much effort applied to it.

Some parts were easy to understand - the worked examples helped a lot, while others, with less videos and based on links, required a lot of work, namely because of the specific terminology used.

Some of the critical links, namely for those sections without videos, are not working anymore, which definitely was a cause of major waste of time looking for additional resources, that were not even using some of the key terminology as that used in the assignments.

As cited by many other people, tutor(s) were not seen in any of the Forum Q&A.

This is not a course I would have taken had I known otherwise.

von Yung-Chuan C

29. Apr. 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.

von Justin M

19. Nov. 2021

I wouldn't take this course. I would give a 1 star review if I wasn't so desperate for courses on linear algebra. I'm happy with the methods covered, and I found the first 2 weeks useful practice. However, it seems like the professor spent about 2 hours making the course. There's only about 30 minutes of content, with most of the learning coming from self-study of linked content on other websites. And week 5 doesn't even have any videos, just links to someone else's tutorials.

von Byron H D

2. März 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.

von Raffaello Z

23. Apr. 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.

von Sabrina B

30. Aug. 2021

Fun course, but feels like they don't supply all the necessary information for the latter section of the course. Had to supplement with self found information to complete this course.

von Sean T

7. Mai 2021

I thought this course was not very helpful, especially in the SVD section. Just giving a bunch of readings on SVD was not very useful. I expected more of an explanation.

von Daniela R E

14. Dez. 2020

Mentor didn´t give the last class and the "extra" material wasn´t helpful at all.

von Charles M

14. Jan. 2021

Lack of explanation especially for the last two weeks

von Axel A R Q

2. Juli 2020

Falta mayor explicación y ejemplos

von sri p b r

5. Sep. 2020

Excellent

von Daniel S

23. Nov. 2021

T​his course is obviously home-made. Why the University of Minnesota permitted it to be uploaded to the Coursera platform is something I cannot fathom; it is by far the shabbiest course I have ever reviewed at Coursera. All topics presented are covered much more effectively in other courses. For example, SVD is covered by Nathan Kutz on his youtube AMATH channel, with applications. The economics of MOOCs is still a bit mysterious to me, but both Coursera and UMinn must financially benefit in at least some small way by having this content here, but why rely on Daniel Boley when we have Gilbert Strang, Nathan Kutz, Grant Sanderson, and many more teachers who actually care about imparting knowledge. If you look at his CV, Boley is research-oriented and obviously no longer cares a whit for teaching at this level. What we get is a review and a rather spotty one, at that, aimed at on-campus students in some other area at UMinn itself who have already mastered the topic.

von Ksenia E

13. Apr. 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.