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

4.7

3,459개의 평가

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622개의 리뷰

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....

Dec 23, 2018

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.

Aug 26, 2018

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.

필터링 기준:

교육 기관: Fridah G W K

•Feb 21, 2019

The instructors were great and the length of the videos is bearable.

교육 기관: Ajay S

•Feb 21, 2019

A great course to learn mathematics for machine learning . Learn a lot thanks for providing me financial aid for the course.

교육 기관:

•Feb 21, 2019

All I can say is WOW. This course was outstanding. I learned particularly well from the first (main) lecturer and loved the way he set up the problems graphically with different colors; I simply couldn't stop going through it and really walked away feeling like I understood these concepts much better. Quite excited to check out their other courses as well!

교육 기관: Sameen N

•Feb 22, 2019

It give me basic understanding of vectors and matrices. Understand the concepts of eigen values and eigen vectors and got understanding of how google pagerank works.

교육 기관: Lia L

•Feb 21, 2019

Great teacher!

교육 기관: Khalil z

•Feb 24, 2019

thank you very much for your pure work

교육 기관: Akash G

•Mar 19, 2019

Mathematics for Machine Learning: Linear Algebra ... REVISED

교육 기관: 谢仑辰

•Feb 28, 2019

I really appreciate staff of ICL's effort to bring us such an intuitive and straightforward course. It's totally different from those linear algebra courses I've received in China. From your idea on explaining this course on space and transformation, I started to build a strong foundation about linear algebra, and machine learning.

교육 기관: Saket S

•Mar 23, 2019

This course was very concise and to the point as far as the field of linear algebra in machine learning is concerned.I learned a lot and will also like to take up the next course of this specialization.

교육 기관: Lotachukwu I

•Mar 23, 2019

The course content, structure and tutors are superb. Challenging assignments though

교육 기관: Dhritiman S

•Mar 23, 2019

The course was absolutely fantastic except for the very last week, where I felt the coverage of eigenvectors and page-rank was rushed. At the same time the assignments felt harder.

교육 기관: Jeferson S

•Mar 23, 2019

Such a great first step to machine learning world. This is really useful to build up a strong knowledge base.

교육 기관: Amravi s

•Mar 03, 2019

excellent course

교육 기관: Kevin M

•Mar 25, 2019

Very, very accessible.

교육 기관: Deeparaj A C

•Mar 26, 2019

It was a great course.

교육 기관: Tushar S

•Mar 27, 2019

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교육 기관: Shijing C

•Mar 27, 2019

useful

교육 기관: Wayne C

•Mar 29, 2019

Best presentation of fundamental Linear Algebra I have ever seen, hands down. (I'm an old-timer, reviewing this material to get up to speed on Machine Learning and Data Science.) While teaching the mechanics, the concepts behind them are always reinforced. Thank you for presenting this material in such a meaningful and digestible way. I also greatly appreciate the reverse-transparent-whiteboard which to me is highly preferable to the other methods I have experienced in online courseware.

교육 기관: SWETA K

•Mar 30, 2019

GOOD COURSES

교육 기관: Eric P

•Mar 19, 2019

I really liked the pace of this course. Not too fast, not too slow. I also enjoyed the focus on intuitive understandings and linear algebra in the context of ML.

교육 기관: Syed S A

•Jan 29, 2019

Amazing course with the detailed explaination on why Linear Algebra and Matrices(concepts) are important.

교육 기관: nr7116

•Jan 26, 2019

I had already looked at Khan Academy and 3bluebrown1 before taking this course.

This course packs the best of both in one place.

교육 기관: Marco C

•Jan 27, 2019

Simply great

교육 기관: NEHAL J

•Jan 26, 2019

If you're looking at refreshing your knowledge of linear algebra for machine learning, this is good course to take. Provides just about enough insights to application of linalg in ML.

교육 기관: Volodymyr C

•Jan 27, 2019

Clearly explained and key equations are derived with good step sizes. Quizzes and assignments are challenging (which is good!) and have high expectations for learners (which is really good for my motivation). Overall, I am really enjoying this course.