Chevron Left
Вернуться к Mathematics for Machine Learning: Linear Algebra

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

Оценки: 8,619
Рецензии: 1,747

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.

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.

Фильтр по:

1651–1675 из 1,742 отзывов о курсе Mathematics for Machine Learning: Linear Algebra

автор: chanhee

25 февр. 2020 г.

It is good course for machine learning. But I didn't fully understand the page rank system with damping.

More explanation of damping is needed for the newbie.

автор: Vignesh N M

12 сент. 2018 г.

Transition from explanation of basic to advanced concepts could have been better. There was an assumption that few things was already know to the learner.

автор: Alexander D

7 авг. 2018 г.

Not enough focus on how material connects to machine learning. A case study example would help, as would a very slow, detailed step-by-step illustration.

автор: Santiago M

14 сент. 2020 г.

Nice one. But realized I needed more foundation on this matter. So decided to abandon and level up my topic knowledge in Khan Acadamy. I will be back.

автор: Cindy X

20 дек. 2018 г.

I think this course is a little bit hard for a beginner with python. And I hope that the teacher can talk more about the Machine learning part.

автор: Atish B

24 сент. 2020 г.

Answers to Several questions in Week 5 quiz around eigen values and eigen vectors need to be revisited as they donot appear to be correct.

автор: Amal J

15 июля 2020 г.

The course gives a good beginner-friendly Introduction to Linear Algebra. But the courses could cover a little more topics in LA.

автор: Jorge G

14 авг. 2020 г.

I would give it 3.7, examples are good but the vectors the lecturer draw were no easy to understand because of drawing by hand.

автор: Badri T

29 дек. 2019 г.

The Eigen system could have been better explained. The last quiz was too hard and the concepts required were not covered

автор: Aaron H

17 окт. 2019 г.

Lot of the concepts seemed glossed over and could have used more guided practice and/or linkages to real world problems.

автор: Kate G

19 нояб. 2020 г.

The instructor is skipping a lot of material and the quizzes require working with external sources to be solved.

автор: Matt

24 февр. 2019 г.

This course would be perfect if more elaboration on the maths required to complete the quizzes, was provided.

автор: N s n r

11 дек. 2019 г.

i expected a practical mathematic approach rather than only mathematical approach.but page rank algo is good

автор: Tony M

23 окт. 2020 г.

Good course, but could add extra steps for those a little rusty with algebra, matrices, vectors and so on.

автор: Jared E

26 мая 2018 г.

Overall good, but some nasty difficulty with the programming assignments... especially the last one.

автор: Almir B

15 окт. 2020 г.

The programming part is too confusing for someone that is just starting.

Thanks for the opportunity.

автор: Aniket D B

9 авг. 2020 г.

Everything is good. But I still don't have any idea about how I will use this in Machine learning.

автор: Alberto M

4 апр. 2019 г.

Good material if you want to refresh your knowledge, poor programming assignment support/feedback

автор: Ahmad A R

1 окт. 2019 г.

Repetitive/redundant questions in the assignment and minimal use of coding during the videos

автор: Carlos R T G R

18 мар. 2019 г.

The videos need to be updated, there are quite some errors that are already identified...

автор: rishabh t

5 мая 2020 г.

Explainations was good but some topics was difficult to get may be due to my basics

автор: Adam R

16 нояб. 2018 г.

Some of the quizzes go beyond what is in the videos and often spent ages on them.

автор: Nicholas K

20 апр. 2018 г.

Enough gaps that I finished feeling like I really had no idea what was going on.

автор: David R M

13 июля 2020 г.

Requires an understanding of python that doesn't seem to be expressed anywhere

автор: Jose H C

19 дек. 2019 г.

I did not see any specific application of what was learned to Machine Learning