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

임페리얼 칼리지 런던의 Mathematics for Machine Learning: Linear Algebra 학습자 리뷰 및 피드백

11,368개의 평가

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


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.


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 2,247개 리뷰 중 1826~1850

교육 기관: HARISH A

2018년 12월 22일

Gives a good intro to some of the basic linear algebra - however would have been happier to see more details in the handling of eigen vectors and eigen values.

교육 기관: NGUYEN B D T

2021년 2월 16일

A good summation of Linear Algebra. This course did give an insight into what matrix is, space, and how to apply transformation in a way that is the easiest.

교육 기관: Sagar L

2020년 2월 15일

The course is pretty helpful as a recap for linear algebra and has nice explanations to set up your intuition for the core mathematical concepts of the field

교육 기관: Saarthak K

2023년 1월 25일

the first four weeks were so good and intuitive. But I was left in confusion for most part of week 5 and had to take help of other sources (khanacademy,etc)

교육 기관: Abhradeep M

2022년 8월 24일

Supplemental materials in the form of examples or bullet points with the core algorithm/concept on the topics would be helpful to grasp the material quicker

교육 기관: Andy T

2020년 8월 22일

This was a great course, however you should expect to have some foundation in linear algebra to begin with and use this as a supplement to your knowledge

교육 기관: Achal C

2020년 5월 19일

Great course !! though not it deals everything in depth or covers wider topics it definitely helps with the basics and introduces well to the subject ...

교육 기관: Haris F

2021년 3월 18일

I am very excited to pass this course. The explanation very great but it very hard to achive this certificate in a week. But alhamdulillah i can do it.

교육 기관: Avery W

2019년 11월 4일

This is a great course, but some of the quizzes are quite difficult. If there were more explanation on the quizzes, this course would be just perfect!

교육 기관: Richard E F

2020년 8월 25일

An intersting course. It was let down by the fact that there was no involvement by the staff in answering students questions as far as I could see.

교육 기관: Ali E

2020년 6월 4일

Its such an amazing course that refreshed me quite well. It only needs some solved problems to get used to the way of solving for more applying.

교육 기관: Rahul K

2020년 5월 25일

Course is very well taught and the focus on intuition is super useful. It would be nice to get into advanced topics after the intuition is built

교육 기관: Вернер А И

2018년 3월 10일

Excellent course. Lots of practical examples. Explanations are clear. I would suggest adding a summary of the lectures in form of some document.

교육 기관: Roderick R

2018년 5월 2일

Good course on reviewing linear algebra fundamentals. I greatly appreciated the instructors' teaching styles and made the material practical.

교육 기관: MAMOON A

2020년 4월 30일

The course helps in understanding the linear algebra in all aspects i.e algebraic as well as graphical and finally implementing it in a code.

교육 기관: ACHRAF S

2019년 10월 6일

Good overall, but i regret that the professor lacked deep understanding for some concepts, which made his explanations not clear by moments !


2020년 6월 9일

Assignments are challenging and certainly the course is excellent for a beginner, though faced some issues at some point during assignments.

교육 기관: Deleted A

2019년 8월 4일

Strong basic preparation, but I feel that it stops too short. There should be a module 6 and a module 7 covering intermediate-level topics.

교육 기관: Yue

2018년 6월 8일

The lecture are sometimes confusing. The example are very easy, but the quiz and code we need to do are much more difficult than the example

교육 기관: Patrick F

2019년 1월 28일

Really good course, would recommend! 4 Stars, because there is no written transcript with the Formula and examples in the videos available.

교육 기관: S M A H

2018년 9월 2일

Course is very interesting and informative, but I found a couple of quiz aren't aligned with course material. These things need to improve.

교육 기관: Pablo S V

2021년 1월 2일

Pretty basic, I hope it gets more into machine learning techniques in the next two parts of the course, as this one is just basic algebra

교육 기관: Gajendra S

2020년 6월 12일

Really cool course, the Page Rank part was the only tough deal for me, I liked the overall course, thanks for this amazing experience! :)

교육 기관: Luis M V F

2019년 3월 9일

It would be better if they have more challenging assignments, and if they had a more detailed explanation of some mathematical concepts.

교육 기관: Angelo O

2018년 12월 5일

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