Mathematics for Machine Learning: Linear Algebra(으)로 돌아가기

4.7
별점
10,709개의 평가
2,130개의 리뷰

## 강좌 소개

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....

## 최상위 리뷰

NS

2018년 12월 22일

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

2021년 8월 8일

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

필터링 기준:

## Mathematics for Machine Learning: Linear Algebra의 2,142개 리뷰 중 1701~1725

교육 기관: Rachana A

2020년 8월 23일

I used to think that where are we going to use these matrices eigen values and vectors in real.. and I've got my answer from this course...Thanks to the professors who had given clear view on these topics...

교육 기관: Александр Л

2019년 11월 1일

Great instructors, excellent content. I would like to see more practical use cases of the material (at least as a self-study reading). And please add an explanation behind formulas for the eigenvectors part.

교육 기관: Augustinas S

2019년 7월 3일

Fast paced linear Algebra, perfect to get refreshed. Might be too concise for those who learned Math not in English a few decades ago, will require to browse Forum for additional links to read on the side.

교육 기관: Shaquille M

2019년 2월 4일

Great primer. Covers most of the important themes of LinAlg needed for applying machine learning, and also provides really good intuition. Useful for those wanting to sharpen up before further study of ML.

교육 기관: Deborah H

2020년 11월 2일

Good content, animated and visually-appealing lectures - considering it is mathematics, assignment material and quizzes are helpful for review, but minimal support and feedback for questions or problems.

교육 기관: Putuma P G

2020년 4월 7일

It's a great course as a refresher, but for mostly folks with a lot of time. The assignments are fair, but sometimes it's dive-in kind of stuff, whereby the assignment itself is the instructive example.

교육 기관: Valentinos P

2019년 7월 13일

An outstanding course which builds your mathematical intuition rather to prepare you for mathematical calculations. My opinion is that its contribution is significant in the pool of courses in coursera.

교육 기관: ThomasZhang

2021년 4월 13일

a bit rush course covering the most important part of linear algebra, give me a very good intuition other than mathematic notations! the course might be better to add some explaination on math side!

교육 기관: Deval P

2020년 7월 10일

even though my code was right in the last assignment the grader kept getting timed out. it took 3 days to work and in the end the code was same. the course on the other hand was quite good and easy.

교육 기관: Jorge V

2018년 11월 11일

Great content and direction. Only negative is the sometimes frustrating experience with the Jupyter Notebooks: debugging what has gone wrong is very difficult, due to a lack of good error messages.

교육 기관: Marco K

2020년 3월 30일

Be careful as a beginner in coding. It might be frustrating from time to time. I have spent the majority of my timing on the coding . At the end worthwhile, but did not feel that way at that time

교육 기관: Milan S

2018년 5월 8일

Good, but sometimes it is neccessary to look for supporting materials. I took this course in combination with MIT course in LA and this offered another, more practice oriented, view on the topic.

교육 기관: Tanmoy D

2018년 6월 7일

The course is a great resource to brush up on the fundamentals of linear algebra and learn about the meaning behind the math.It prepares people for any further courses which use linear algebra.

교육 기관: Keshav B

2020년 6월 13일

This course was very insightful. The instruction was well done with expressing the intuition, but the process was left vague on a few concepts and required me to look up worked out examples.

교육 기관: Lalpekhlua L

2021년 7월 17일

I think it is a great course. It is definitely not for beginners and I feel the lectures are somewhat rushed on some videos. It is best to view this course as a supplement and not as a main

교육 기관: Sharon I

2022년 3월 27일

good videos and good instructors; programming assigments could be a little bit clearer in the instructions. Overall good for understanding the maths behind Machine Learning. Thank you!

교육 기관: shashank s

2020년 2월 17일

The course was good but it could have been better if the exercises had more difficult questions or probably a section with more difficult questions using the concepts that were taught.

교육 기관: ASIFIWE E

2021년 3월 2일

This is excellent course provided as fundamental skills required in Machine learning journey. I was excited to be learn from best lecturers ever and, thanks to Imperial College.

교육 기관: Gurudu S R

2019년 8월 18일

1.Need more clarity on calculating Eigen vectors using back substitution of Eigen values.

2. Power Iteration method for the Page Rank Algorithm should be more specific and clear.

교육 기관: Phuong N

2018년 9월 24일

The course can help me more clearly when approach some algorithms in the optimize function of Machine learning. Thanks coursera and Imperial London College about this course.

.

교육 기관: Tom F

2021년 12월 28일

A really well structured course, a few minor problems with the coding assignment formatting but otherwise all the topics were covered in depth with plenty of application tests.

교육 기관: Sri C D

2020년 7월 16일

The instructors and the way of their explanation are a huge benefit of this course. The intuition they provided each step in Linear and Vector Algebra are really appreciable.

교육 기관: Elliott P

2019년 4월 30일

It's a very good course given that it's so short. It was exactly what I was expecting. I thought it could have had more examples of solving problems with specific techniques.

교육 기관: Sastry

2018년 4월 11일

Very interesting presentation of matrices and vectors. The questions in quizzes could be improved by making them clear. May be you could add another course on eigen analysis.

교육 기관: NAVEEN R

2020년 8월 2일

Topics are explained neatly but lacked in depth explanation in few topics and i suggest to include more application oriented examples to every topics covered in the course.