Chevron Left
Back to Mathematics for Machine Learning: Linear Algebra

Learner Reviews & Feedback for Mathematics for Machine Learning: Linear Algebra by Imperial College London

4.7
stars
12,533 ratings

About the Course

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....

Top reviews

DV

Jun 24, 2019

This was a terrific course; the instructors' are passionate and knowledgeable about the course material, the assignments are engaging and relevant, and the length of the videos feels "just right".

LK

Oct 26, 2023

Very good course. I liked very much the way the topics were presented and explained. I especially appreciate David Dye's clarity of explanations, enthusiasm, passion, and joyful attitude. Thank you.

Filter by:

1751 - 1775 of 2,477 Reviews for Mathematics for Machine Learning: Linear Algebra

By Sreeprakash N

•

Nov 10, 2019

Very good

By Prabal G

•

Oct 10, 2019

very good

By Jorge H L B

•

Oct 7, 2019

Excelente

By Greg H

•

Jun 18, 2019

Very Good

By Sasikumar G

•

May 23, 2019

Excellent

By Colin W

•

May 15, 2019

Excellent

By Fabrice M

•

Apr 14, 2019

Excellent

By Xinya X

•

Mar 13, 2019

I like it

By DIVYANSH S

•

Feb 4, 2019

excellent

By Edward K

•

Sep 17, 2018

very nice

By 海鹿

•

Mar 16, 2018

excellent

By Tanuj

•

Oct 31, 2025

all good

By Karta K

•

Mar 18, 2023

Amazing!

By Nicolas C

•

Feb 2, 2023

Awesome!

By Sukhvir S

•

Aug 23, 2020

NIce One

By HALIKHEDE S S

•

Aug 19, 2020

best one

By Isaac M M

•

Jul 24, 2020

Excelent

By Yoshiaki K

•

Jun 9, 2020

Awesome!

By MOHAMMED F R

•

May 29, 2020

its good

By Deleted A

•

Jan 26, 2020

Perfect!

By Xiaxin

•

Oct 5, 2019

可以听得懂的课程

By Kanishka A

•

Apr 24, 2025

Amazing

By Võ H K K D

•

Mar 26, 2025

So good

By Insyiraah O A

•

Mar 21, 2022

mantaps

By Raphy

•

Feb 6, 2022

perfecy