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

11,374 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....



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.


31. März 2018

Amazing course, great instructors. The amount of working linear algebra knowledge you get from this single course is substantial. It has already helped solidify my learning in other ML and AI courses.

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1951 - 1975 von 2,249 Bewertungen für Mathematics for Machine Learning: Linear Algebra

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.

von Rocber

30. Sep. 2018

it is really useful to help me build geometric meaning with vector and matrix.

von phanidhar s

1. Juni 2020

The course will help us to apply the matrices for machine learning algorithm.

von Benjamin W

16. Juli 2021

Some of the autograding wasn't great but the discussion forums helped a lot

von Tarun A

21. Mai 2020

after learn from this course, i know very well about machine learning


von Aviral A

10. Dez. 2018

A good course for gaining knowledge for Linear Algebra for machine learning.

von 胡与诚

2. Apr. 2018

Good course, But I think it should explain more about the underlying things.

von Timur S

20. Sep. 2022

It is not basic course and requires prior knowledge of the topis discussed

von Alfian A H

3. März 2021

Overall is good. But somehow, there are parts that I don't understand well.

von Bruna R

6. Feb. 2021

the course is excellent. I have learned a lot and it was very interactive.

von Gundepudi V

13. Juli 2020

Was a but fast. For non engineering or people who are new it will be tough

von Abhirup B

29. Juli 2020

goood course well designed qizes and aasignments time saving yet fruitful

von Julian A

12. Juni 2020

Fantastic course that provides a great introduction into linear algebra.

von Ivan

4. Juni 2018

The course content is good, but the programming assignment is too easy.

von Ritik j

1. Juni 2020

some topics are explained in a typical way and a bit problem was occur

von I M N P M

24. Feb. 2021

The eigen value and eigen vector courses are a bit hard to understand

von Kevin O

25. Feb. 2021

A good refresher with some really useful insights about eigenthings.


21. Juli 2020

Its is the best course to know about matrices and their applications

von KURRA S S 2

26. Dez. 2022

It is so useful to me for getting the knowledge in machine learning

von Sharad K L

9. März 2020

Exams were hard and most of the exams were source of the knowledge.