Вернуться к Mathematics for Machine Learning: Linear Algebra

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

4.7
звезд
Оценки: 10,272
Рецензии: 2,060

## 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

NS
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.

HE
8 авг. 2021 г.

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

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## 1776–1800 из 2,068 отзывов о курсе Mathematics for Machine Learning: Linear Algebra

автор: Berkay E

26 июля 2019 г.

Some of the concepts are unclear. You need to make extra research to understand whole concepts.

автор: Liang Y

16 апр. 2019 г.

Very good I learn a lot though I get confused in Week 4 about E @ TE @ inv(E). Thank you profs!

автор: Vinayaka R K

15 авг. 2020 г.

The eigwn vector parts could've been much much better, rest apart assignments were really good

автор: Mohamed A A

23 июня 2020 г.

very good for beginners who want to understand what happens in machine learning under the hood

автор: Md. M I

3 мая 2020 г.

A little more assignments might be good towards the end. Otherwise, it is an excellent course.

автор: Alexander D K

21 авг. 2019 г.

Fairly good introductory course but not a substitution for a proper LA course for ML purposes.

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

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: bowman

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: Peeyush S K

20 нояб. 2021 г.

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

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.