Вернуться к Mathematics for Machine Learning: Linear Algebra

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

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Оценки: 9,678
Рецензии: 1,949

## 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

EC
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.

PL
25 авг. 2018 г.

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.

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## 1726–1750 из 1,939 отзывов о курсе Mathematics for Machine Learning: Linear Algebra

автор: 谢迟

25 июня 2018 г.

The core idea of eigenvalue and eigenvector is very good.

автор: Andini a

12 мар. 2021 г.

I thought it was lacking in practice before the LAB test

автор: stark

6 февр. 2021 г.

Inspired me how to look at matrix, but not deep enough

автор: Alisa G

25 апр. 2020 г.

great teachers, very practical quizzes and examples!

автор: Long Q

10 окт. 2018 г.

not bad, I feel the information is not enough for ML

автор: Rahul S

21 июня 2020 г.

like a building blocks for one step forward into AI

автор: Aniruddhan P N

29 мая 2020 г.

Excellent Introduction to the concepts, Thank you!

12 февр. 2019 г.

reasonably well constructed and presented material

автор: Abhishek J

19 апр. 2020 г.

Good Course, Best Videos, Excellent Understanding

автор: Manish C

16 апр. 2020 г.

well made course for machine learning foundation

автор: Tasfiq R

29 июня 2020 г.

Great course.Animation can be addes for pagerank

автор: Kasidit ( R

21 мар. 2019 г.

Great way to build foundation in Linear Algebra

автор: Jay S S

27 июля 2020 г.

Fast paced interesting course. Lots to learn!

автор: Uri M

29 сент. 2020 г.

Pretty nice hands on linear algebra course

автор: 何霄

23 февр. 2020 г.

clearly explain all the key concepts in la

автор: Ratnakar

1 июня 2018 г.

Very engaging course and right on spot!!!

автор: Andres O

25 мая 2018 г.

Very good linear algebra intro/refresher

автор: Paul M D C B

2 нояб. 2020 г.

Too technical but relevant nonetheless

автор: Manikanta G

22 авг. 2020 г.

it's worth taking to revise the topics

автор: Richard P

15 июля 2020 г.

Great knowledge at an affordable price

автор: Salah E

30 июня 2020 г.

it is very hard course yet very useful

автор: Nirmala R

3 июня 2020 г.

Week 5 was bit difficult to comprehend

автор: Ritwik M

17 мая 2020 г.

Prof. Sam is a bit hard to understand.

автор: danthedoubleD

22 февр. 2019 г.

good stuff hopefully, i will be useful

автор: Annamma A

30 нояб. 2020 г.

Help with programming should be given