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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: 9,591
Рецензии: 1,936

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

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.

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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1601–1625 из 1,928 отзывов о курсе Mathematics for Machine Learning: Linear Algebra

автор: Angelo S d O

5 дек. 2018 г.

Nice refresher! Excellent instructors! Not recommended as a first Linear Algebra course though. I would go for MIT OpenCourseware first.

автор: Lasal J

6 нояб. 2020 г.

All the first four weeks were well comprehensive and clear. Week 5 (last week) on eigenvalues seemed rushed and could have been better.

автор: Jitendra S R

23 дек. 2019 г.

This is really a very good course. To the point explanations. No more no less. Assignment Notebook links do have some problems though.

автор: Mohamed B

27 авг. 2019 г.

The concepts are explained clearly, but someone who has already done some machine learning before might find some parts unchallenging

автор: Aditya J

16 мар. 2020 г.

Overall great. But can get tough to follow at times and feel that more and in-depth explanation would be required at certain places.

автор: Cirus I

27 авг. 2018 г.

A fun way to review Linear Algebra basics focused on its applications on Machine Learning.

Good structure, nice pace, solid content.

автор: Keyuan W

8 июля 2019 г.

Basic knowledge about machine learning, but very useful, maybe this course should be tagged as higher level, instead of beginner.

автор: Valeria

26 июня 2018 г.

I really enjoyed how much graphical explanation there was here. It finally starts making sense why we use matrices and vectors.

автор: Mobarak H S

13 апр. 2020 г.

The quiz challenge was good for me to better understand this course. And the length of video enough short to not to feel bore.

автор: Ahmad A A D

11 нояб. 2020 г.

this course is good for giving introduction, but for depth understanding you should accompany with another resource materials

автор: Joanna M

6 апр. 2021 г.

Great course, but there are some bugs in automatic assignment grading, and the instructors are not responsive on the forums.

автор: Sherina M

11 мар. 2021 г.

The difficulty of the problem in the quiz and the example in the video is too far, the problem in the quiz is so much harder

автор: Jayaram O

14 июня 2020 г.

Important concepts of Linear Algebra for ML explained in a beautiful multi-dimensional method including theory and practice.

автор: Dharv P

22 июля 2020 г.

Very Good Course, You will learn linear algebra in this course and most loved part of course for me is pagerank assignment.

автор: Peter S

8 окт. 2020 г.

A good course with some significant leaps in competence required for those of us with a social science/business background

автор: Kartikeya S

2 июня 2020 г.

Course was nice,but if you provide more example of real world usage of Linear Algebra in Machine Learning it would be nice

автор: Rahul B

22 апр. 2020 г.

This was course made my intuition for underlying mathematics when using machine learning much more stronger and efficient.

автор: Muhammad E

8 авг. 2020 г.

the course is a bit challenging i would recommend that you better get yourself familiar with basic linear algebra first

автор: Sudhir N

31 мая 2019 г.

Good refresher for basic concepts learnt in the University ages ago. WOuld like to have more real life Business examples

автор: jiang y

15 авг. 2020 г.

this is a very nice and useful lesson.

but sometime I need to search for more knowledge to help me finished my home work

автор: Dhruv A

31 июля 2020 г.

Brilliantly conducted. Provides a great introduction to linear algebra allowing the learner to start diving in further.

автор: Daniel T

18 июня 2019 г.

It would be better if it had lecture notes. Reviewing the material and writing it down requires rewatching the lectures

автор: Robert S

18 авг. 2018 г.

The linear algebra was taught in an easy to understand manor but the applications in machine learning were quite sparse

автор: Marcos G A

7 июля 2020 г.

Should share additional videos (like links to khan academy if the student needs to learn more or wants to get deeper).

автор: Weiyu G

12 авг. 2019 г.

It is really intuitive and good for people who have little idea of Linear Algebra. The best part is the PageRank Algo.