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

4.7
Sterne
11,336 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

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.

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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1751 - 1775 von 2,242 Bewertungen für Mathematics for Machine Learning: Linear Algebra

von Jean S

20. Aug. 2019

Excellent course and very practical; it's really focused on machine learning and there's the opportunity to learn some coding in Python. I would recommend it to everyone interested in machine learning. I give it 4 stars because there's always room to improve.

von Yaroslav K

2. März 2020

As I person who have 2 Masters Degrees in Law and Agriculture this course sometimes was to challenging. May be it's good reminder for those who have some strong math background, but you'll need to read and watch all lot of additional material in another case.

von 04_RitikDhama

1. Mai 2020

Course was very interesting but found some difficulties in the assignment section as it took almost hour to understand it. But, the course was very nice and also it help me to recollect all the mathematics part of Linear Algebra that I've studied earlier.

von Aarón M C M

5. Juni 2019

I am a computer scientist and this course served me to refresh all that concepts and exercises that I studied at the university, I only would ask to improve of the notebook's availabilty because sometimes I got disconnected and had to start all over again.

von Akiva K S

30. Mai 2020

Multiplying 2x2 matrices by hand drives me crazy! Why instructors waste precious online time on that crap? Two, three matrix multiplications by hand during the lecture is perfectly OK with me, but why to do it over and over? The same with the exercises.

von Xiaocong Y

15. Feb. 2021

Good for beginner, but relatively easy if you have backgrounds in Linear Algebra. The course focus on making you adopt intuitions of how Linear Algebra is actually working geometrically which may be interesting if you only knows how the algebra works.

von Joshua P

9. Juli 2020

As someone with a bit of a background in linear algebra, this course is perfect in being a refresher to the said course. But unfortunately, especially for those who are completely new to the subject, the hurried explanations will leave some confused.

von Jehan T

9. Aug. 2020

Great course, especially the first 4 weeks with David Dye. Unfortunately the lecturer in the 5th week is much harder to follow, and I needed to reference some additional youtube videos outside the course to get an intuitive grasp of the concepts.

von David B C

8. Sep. 2018

Great lectures and wonderful scrutiny of matrices and vectors. Exploration of machine learning using Python, but the interface and project upload are somewhat kludgy. Stick with it and you can get the fundamentals even if the coding doesn't work.

von Priadi T W

7. Sep. 2019

The course was great for me. It opens up new perspective to some vector and matrix application. However, I must admit that you must have strong background with math before taking this course, as I was little bit struggling with matrix part.

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 Luis S

28. Okt. 2022

The course is good to develop the intuition around linear algebra. However, some important concepts are not sufficiently developed to have a complete understanding of the course. I had to find other sources to complement this course.

von Godugu A H

30. Nov. 2021

The 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.