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Bewertung und Feedback des Lernenden für Mathematics for Machine Learning: Linear Algebra von Imperial College London

4.7
Sterne
11,446 Bewertungen

Über den Kurs

In this course on Linear Algebra we look at what linear algebra is and how it relates to vectors and matrices. Then we look through what vectors and matrices are and how to work with them, including the knotty problem of eigenvalues and eigenvectors, and how to use these to solve problems. Finally we look at how to use these to do fun things with datasets - like how to rotate images of faces and how to extract eigenvectors to look at how the Pagerank algorithm works. Since we're aiming at data-driven applications, we'll be implementing some of these ideas in code, not just on pencil and paper. Towards the end of the course, you'll write code blocks and encounter Jupyter notebooks in Python, but don't worry, these will be quite short, focussed on the concepts, and will guide you through if you’ve not coded before. At the end of this course you will have an intuitive understanding of vectors and matrices that will help you bridge the gap into linear algebra problems, and how to apply these concepts to machine learning....

Top-Bewertungen

NS

22. Dez. 2018

Professors teaches in so much friendly manner. This is beginner level course. Don't expect you will dive deep inside the Linear Algebra. But the foundation will become solid if you attend this course.

EC

9. Sep. 2019

Excellent review of Linear Algebra even for those who have taken it at school. Handwriting of the first instructor wasn't always legible, but wasn't too bad. Second instructor's handwriting is better.

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1851 - 1875 von 2,266 Bewertungen für Mathematics for Machine Learning: Linear Algebra

von Avery W

4. Nov. 2019

This is a great course, but some of the quizzes are quite difficult. If there were more explanation on the quizzes, this course would be just perfect!

von Richard E F

25. Aug. 2020

An intersting course. It was let down by the fact that there was no involvement by the staff in answering students questions as far as I could see.

von Ali E

4. Juni 2020

Its such an amazing course that refreshed me quite well. It only needs some solved problems to get used to the way of solving for more applying.

von Rahul K

25. Mai 2020

Course is very well taught and the focus on intuition is super useful. It would be nice to get into advanced topics after the intuition is built

von Alexander V

10. März 2018

Excellent course. Lots of practical examples. Explanations are clear. I would suggest adding a summary of the lectures in form of some document.

von Roderick R

2. Mai 2018

Good course on reviewing linear algebra fundamentals. I greatly appreciated the instructors' teaching styles and made the material practical.

von MAMOON A

30. Apr. 2020

The course helps in understanding the linear algebra in all aspects i.e algebraic as well as graphical and finally implementing it in a code.

von ACHRAF S

6. Okt. 2019

Good overall, but i regret that the professor lacked deep understanding for some concepts, which made his explanations not clear by moments !

von ASHIRWAD R

9. Juni 2020

Assignments are challenging and certainly the course is excellent for a beginner, though faced some issues at some point during assignments.

von Deleted A

4. Aug. 2019

Strong basic preparation, but I feel that it stops too short. There should be a module 6 and a module 7 covering intermediate-level topics.

von Yue

8. Juni 2018

The lecture are sometimes confusing. The example are very easy, but the quiz and code we need to do are much more difficult than the example

von Patrick F

28. Jan. 2019

Really good course, would recommend! 4 Stars, because there is no written transcript with the Formula and examples in the videos available.

von S M A H

2. Sep. 2018

Course is very interesting and informative, but I found a couple of quiz aren't aligned with course material. These things need to improve.

von Pablo S V

2. Jan. 2021

Pretty basic, I hope it gets more into machine learning techniques in the next two parts of the course, as this one is just basic algebra

von Gajendra S

12. Juni 2020

Really cool course, the Page Rank part was the only tough deal for me, I liked the overall course, thanks for this amazing experience! :)

von Luis M V F

9. März 2019

It would be better if they have more challenging assignments, and if they had a more detailed explanation of some mathematical concepts.

von Angelo O

5. Dez. 2018

Nice refresher! Excellent instructors! Not recommended as a first Linear Algebra course though. I would go for MIT OpenCourseware first.

von Lasal J

6. Nov. 2020

All the first four weeks were well comprehensive and clear. Week 5 (last week) on eigenvalues seemed rushed and could have been better.

von Jitendra S R

23. Dez. 2019

This is really a very good course. To the point explanations. No more no less. Assignment Notebook links do have some problems though.

von Mohamed B

27. Aug. 2019

The concepts are explained clearly, but someone who has already done some machine learning before might find some parts unchallenging

von Aditya J

16. März 2020

Overall great. But can get tough to follow at times and feel that more and in-depth explanation would be required at certain places.

von Cirus I

27. Aug. 2018

A fun way to review Linear Algebra basics focused on its applications on Machine Learning.

Good structure, nice pace, solid content.

von Gurbaaz S G

13. Mai 2021

The course was informative and helpful. it helped me bring back concepts that I had forgot and also taught me a bit about python.

von Alex W

8. Juli 2019

Basic knowledge about machine learning, but very useful, maybe this course should be tagged as higher level, instead of beginner.

von Valeria

26. Juni 2018

I really enjoyed how much graphical explanation there was here. It finally starts making sense why we use matrices and vectors.