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學生對 伦敦帝国学院 提供的 Mathematics for Machine Learning: Linear Algebra 的評價和反饋

4.7
4,359 個評分
778 個審閱

課程概述

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....

熱門審閱

NS

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.

EC

Sep 10, 2019

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.

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201 - Mathematics for Machine Learning: Linear Algebra 的 225 個評論(共 776 個)

創建者 liyimeng

Jun 18, 2018

It's really helpful to rebuild the fundamental, not very deep enough. It's better to read some books as well when take the course

創建者 Rui_Lian

May 25, 2018

Many thanks for David and Samuel! I've been struggling with linear algebra for quite a long time. I can do the math, but I get lost when I try to use linear algebra to understand something in statistics and machine learning. The intuition based approach is perfect. I like the apple-banana example, I like the transformation and visualization of eigenvector in 2 dimension. Also, the page rank case is quite cool and thought provoking.

I think I will stay on this series for following two courses.

Thanks again!

創建者 Danielius K

May 23, 2018

An amazing introduction to a crucial part of machine learning!

創建者 Mansur A

Jun 18, 2018

Insightful and challenging, excellent course! Thanks for delivering this awesome course

創建者 Christopher H

Mar 31, 2018

Great intro

創建者 Arnaud J

May 12, 2018

Nice introduction or freshener on linear algebra.

創建者 Jurij N

Jun 18, 2018

I was very satisfied with the course. I'm really grateful for the effort they put into the programming exercises, so I finally began to put the theoretical knowledge into code. From now on I am able to experiment by myself.

創建者 Alexander v d P

May 22, 2018

Very clear quick browse through some concepts from linear algebra

創建者 Art P

Jun 08, 2018

This course was of high quality, was very helpful in explaining some key concepts and I appreciated the instructors energy and humor. My only complaint about the course is that some of the quizzes and homework assignments felt significantly more challenging than what was covered in the lessons; however, the discussion forums proved helpful in closing this gap.

創建者 HARSH K D

Jun 13, 2018

nice of mathematics

創建者 Huang X

May 12, 2018

This course helps me a lot. I don't need to calculate the matrix by hand. I just need to get the concept of what is the matrix doing and use computer to calculate it. This is the most import thing I got in this course.

創建者 Christos P

Jul 02, 2018

It was honestly great. The first two weeks didn't have much new for someone who'd already taken Linear Algebra, but the last three weeks were very informational. It really helped me understand the concepts geometrically/spatially in ways I hadn't seen before when I had taken general linear algebra at my university.

創建者 Wang Z

Jun 30, 2018

Very challenging yet extremely beneficial

創建者 Keer M

Jun 03, 2018

Informative and not overbearing. Does a good job connecting lecture material with practical problems.

創建者 Niclas F S

Apr 14, 2018

Superb introduction to Linear Algebra! Thanks to the instructors for their very clear explanations!

創建者 Anas N B

Jun 06, 2018

Very Useful to understand clearly the Linear Algebra Basics.

Thanks u professor.U did a great job.:)

創建者 Sai S H G

Apr 26, 2018

Really enjoyed the course!

Wonderful lectures and really helpful assignments.

創建者 Nanyan Z

May 25, 2018

It's really useful!

創建者 Deepak T

May 07, 2018

Awesome explanation of each topic!!

創建者 Shanxue J

Apr 01, 2018

Truly exceptional course. Strongly recommend!

創建者 Lisa M

Apr 07, 2018

This was a fantastic course. I'm new to linear algebra, so it was bit intimidating even signing up (!) - but the lecturers were really, really good about explaining all concepts from the ground up so it was always possible to visualize and extrapolate from solid foundations. For me it was a stretch each week, but in a good way: very challenging, but achievable with enough planning and effort.

創建者 Thomas F

Apr 19, 2018

Highly valuable introduction to linear algebra. Maybe the programming assignments are far too easy, while some of the quizzes definitely are hard. And the best part of the course was to introduce www.3blue1brown.com with it's videos on youtube.

創建者 Liam M

Apr 04, 2018

This is an excellent refresher of vectors and linear algebra, and although I did it years ago in college I still found some new insights from doing this course. Its all explained very well without being bogged down in formailty.

創建者 Joshua S

Apr 21, 2018

Great introduction to linear Algebra! Wish my college experience was this good! I highly recommend an iPad Pro and Apple pencil to take notes. Man this is awesome.

創建者 Nigel H

Apr 18, 2018

Very high production standards, well presented by enthusiastic staff and very manageable as the material is taught so well. Highly recommended.