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Вернуться к Mathematics for Machine Learning: Linear Algebra

Отзывы учащихся о курсе Mathematics for Machine Learning: Linear Algebra от партнера Имперский колледж Лондона

Оценки: 9,675
Рецензии: 1,948

О курсе

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....

Лучшие рецензии

22 дек. 2018 г.

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.

9 сент. 2019 г.

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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1676–1700 из 1,939 отзывов о курсе Mathematics for Machine Learning: Linear Algebra

автор: MIGUEL A G H

27 дек. 2020 г.

Very usefull to deep in the mathematical foundations of machine learning. Very recommendable.

автор: Andrew X

2 нояб. 2020 г.

In week 5, some practice questions seems a little irrelevant to the key mathematical concepts

автор: Aditya G

2 сент. 2019 г.

The course is really nice. A bit of programming experience is needed to complete this course.

автор: Nishant A

4 июня 2018 г.

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

автор: w w

24 июля 2020 г.

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

автор: Utkarsh L

15 мая 2020 г.

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

автор: George P

12 апр. 2020 г.

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

автор: Elnur M

8 апр. 2020 г.

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

автор: Hayder M A

25 апр. 2020 г.

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

автор: parikshit s

16 февр. 2020 г.

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

автор: Antoine P

20 янв. 2021 г.

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

автор: Akhil C

31 мая 2020 г.

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

автор: Zhejian C

20 янв. 2020 г.

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

автор: Andrew K

17 февр. 2019 г.

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

автор: Vinayak k

7 июня 2020 г.

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

автор: Michał K

29 нояб. 2019 г.

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

автор: Max W

2 мар. 2020 г.

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

автор: Robin S

17 февр. 2020 г.

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

автор: Kyle B

23 сент. 2020 г.

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

автор: Hamza K

30 нояб. 2019 г.

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

автор: Debzani M

29 апр. 2020 г.

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

автор: Deleted A

19 июля 2019 г.

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

автор: Hariharasudhan A S

12 февр. 2019 г.

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

автор: Zhuocheng Y

2 дек. 2018 г.

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

автор: Xinsong D

14 июня 2018 г.

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