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

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10,788 Bewertungen
2,149 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

HE

8. Aug. 2021

the instrutors were too good and their explination for the concepts was to the point and it made me realize things in linear algebra I didn't know before although I studied it in school of engineering

CS

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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1701 - 1725 von 2,161 Bewertungen für Mathematics for Machine Learning: Linear Algebra

von Marcin

4. Juni 2018

It's by far the toughest course that I've done on Coursera. And at the same time the most rewarding upon completion. The course content is very applicable in the real world and it's definitely something that any ML specialist should know.

von Srinivas A

7. Juli 2020

Great content, well explained, it's an overview of Linear Algebra relevant to Machine Learning, not a full blown course. Some of the assignments need clarity, especially the Python assignments. There is no faculty/staff to ask questions.

von Mikko V

1. Aug. 2018

The lectures are excellent, but the scarcity of traditional math assignments prevented intuitive and reinforced learning. Thus the course should be considered a brief glance at linear algebra, rather than a proper course on the subject.

von Yadla V C

19. Okt. 2020

This Course takes you to the deep dive of Linear Algebra. But the lectures are not sufficient to solve assignments. We can make use of the resources given by Instructors for clear understanding of core concepts of Vectors and Matrices

von Godugu A H

30. Nov. 2021

T​he course overall is very good. The only drawback I felt was the lack of numerical examples to intepret complex linear algebra formulae. I would love to see videos carrying more worked examples of the formulae learnt in the course.

von Gady

26. März 2020

The pedagogy could use some reviewing, but the concepts and especially the reviews are generally laid out logically, and relatively easy to go through. Still recommend looking up things on the side through YouTube when you're stuck.

von Rohit S

3. März 2020

There were many concepts which were totally new to me and many were known to me but I couldn't relate them with the machine learning problems now an I am able to do all those problems easily so thanks a lot Coursera and ICL team.

von Akshay V

14. Juli 2020

It is a good course on Linear Algebra. The teaching was excellent, all the assignments were challenging with some easy ones in the middle to boost your learning process, altogether I am happy to cover it with good understanding.

von Mit S

24. Feb. 2020

This course has great content and great way of teaching by instructors however the instructions in the programming exercises is not very clear. I hope the instructors take note of that. Overall, a fantastic Course content wise!

von Sekhar G

20. Aug. 2020

Being at an advance level of study, this course seems to easy to me but what I recommend is that any undergraduate or postgraduate student will definitely gain many interesting facts about linear algebra from this course.

von Carlos M V R

25. Juli 2020

It could be good to have more explanation about eigenvalues and eigenvectors because it is an important topic for data science. In general it is a very good course, you explained many topics in a simple and funny way.

von Arnab S

21. Juni 2020

I enjoyed learning in this course. There are a lot of different aspects that are covered here which is very interesting but I course is not for absolute beginners. It will be better if someone has a bit of background.

von Bassiehetkoekje

27. Feb. 2019

Nicely structured courses with enthusiastic teachers. Interactive enough to keep you thinking (which is key).

Some errors here and there and short moments of not enough explanation. But all in all an enjoyable course.

von Naser A A

11. Juli 2020

Great course to understand how linear algebra is related to machine learning. Focused on the concepts, and the concepts work rather than calculations. Would be easier if there was prior knowlodge of python and numpy.

von Cici

12. Juli 2019

This is a great course. The only thing is sometimes the calculations are hard to follow. I wonder if it is possible to let viewers click through a calculation process at their own pace. But the instructors are great!

von Mrunal U

20. Juli 2020

excellent course to understand the linear algebra as a tool for problem solving in machine learrning though it not help directly but give you the strong understanding the fundamentals which will help in the future

von Snigdha A

13. Okt. 2020

Excellent course. I just wish the assignments were a little harder. The last assignment was the perfect toughness level. Made me connect concepts, look up stuff and actually get out of my comfort zone to learn.

von Rachana A

23. Aug. 2020

I used to think that where are we going to use these matrices eigen values and vectors in real.. and I've got my answer from this course...Thanks to the professors who had given clear view on these topics...

von Александр Л

1. Nov. 2019

Great instructors, excellent content. I would like to see more practical use cases of the material (at least as a self-study reading). And please add an explanation behind formulas for the eigenvectors part.

von Augustinas S

3. Juli 2019

Fast paced linear Algebra, perfect to get refreshed. Might be too concise for those who learned Math not in English a few decades ago, will require to browse Forum for additional links to read on the side.

von Shaquille M

4. Feb. 2019

Great primer. Covers most of the important themes of LinAlg needed for applying machine learning, and also provides really good intuition. Useful for those wanting to sharpen up before further study of ML.

von Deborah H

2. Nov. 2020

Good content, animated and visually-appealing lectures - considering it is mathematics, assignment material and quizzes are helpful for review, but minimal support and feedback for questions or problems.

von Putuma P G

7. Apr. 2020

It's a great course as a refresher, but for mostly folks with a lot of time. The assignments are fair, but sometimes it's dive-in kind of stuff, whereby the assignment itself is the instructive example.

von Valentinos P

13. Juli 2019

An outstanding course which builds your mathematical intuition rather to prepare you for mathematical calculations. My opinion is that its contribution is significant in the pool of courses in coursera.

von ThomasZhang

13. Apr. 2021

a bit rush course covering the most important part of linear algebra, give me a very good intuition other than mathematic notations! the course might be better to add some explaination on math side!