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

4.7
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11,348 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.

PL

25. Aug. 2018

Great way to learn about applied Linear Algebra. Should be fairly easy if you have any background with linear algebra, but looks at concepts through the scope of geometric application, which is fresh.

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1926 - 1950 von 2,243 Bewertungen für Mathematics for Machine Learning: Linear Algebra

von Nishant A

4. Juni 2018

Brilliant brush up course. Could have had a little more about eigen vectors and eigen values

von bowman

24. Juli 2020

it's an execlent course, but week5 should be extend to make it clear and easy to understand

von Utkarsh L

15. Mai 2020

Some video lectures should be there which will give some ideas about how to do programming.

von George P

12. Apr. 2020

Excellent course as a refresher if you've studied Physics and need to recover the content

von Peeyush S K

20. Nov. 2021

Teaching Style and the Teaching Aids were very effective. Personally I liked the course.

von Elnur M

8. Apr. 2020

I think it would be better if you add Singular Value Decomposition concept into syllabus

von Hayder M A

25. Apr. 2020

Very useful materials and the instructors are very good and make it easy to understand.

von parikshit s

16. Feb. 2020

Really Good course, learnt a lot of things, just wanted this course to be in more depth

von Antoine P

20. Jan. 2021

Really intersting. Could be a bit difficult for people without mathematical background

von akhil

31. Mai 2020

Sam part wasn't so impressive. Really loved the way David has gone through the course.

von Zhejian C

20. Jan. 2020

Teach good intuition and good explanations but maybe a bit shallow, good for beginners

von Andrew K

17. Feb. 2019

great visual explanations of concepts, but the course could have been more informative

von Vinayak k

7. Juni 2020

Very good insight of linear algebra. It give different prospective of linear algebra.

von Michał K

29. Nov. 2019

Good course, advise to take it, though sometimes not everything explained thoroughly!

von Max W

2. März 2020

excellent approach to linear algebra, high quality and carefully thought out lessons

von Robin S

17. Feb. 2020

Very nice course. A good math overview with a balance between details and practice.

von Kyle B

23. Sep. 2020

Good course, Its a very good basis to build a math foundation for machine learning

von Hamza K

30. Nov. 2019

Instructor should give more example related to Data Science and Machine Learning.

von saksham k

17. Okt. 2022

Everything is amazing, just they need to expalin their solution in a better way.

von Debzani M

29. Apr. 2020

An organized course, great for developing the imagination of mathematics and fun.

von Deleted A

19. Juli 2019

Really intuitive course on matrix algebra with very clear geometric explanations.

von Nicholas J F

27. Sep. 2021

Good overview. I definitely had to go to outside material for the Row Reduction.

von Hari

12. Feb. 2019

A good introduction, would recommend referring a textbook along with the course.

von Zhuocheng Y

2. Dez. 2018

The programming grading system doesn't work well, but the course is great anyway

von Xinsong D

14. Juni 2018

Excellent, but for the pagerank part, the instructor teaches a little bit fast.