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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
10,142 ratings
2,041 reviews

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

PL
Aug 25, 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.

HE
Aug 8, 2021

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

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476 - 500 of 2,048 Reviews for Mathematics for Machine Learning: Linear Algebra

By Wookjae M

May 2, 2019

It was a "neat" lecture for understanding the basic of linear algebra. Programming assignments and test were well designed. Thank you for the lecturers.

By Gabriela S

Nov 3, 2019

Great approach, teaching the intuition of mathematics, this is exactly what I was looking for! Thank you to the amazing instructors for the fun course!

By Nuria C

Nov 3, 2020

Really well explained. I wish I had got such a professor when I learn these concepts in the highschool :) Lot's of examples and exercises to practice.

By Gupta, N - N

Apr 29, 2021

Really good introductory course for linear algebra, specially for people who found it difficult during university and now looking to revise it for ML

By Maksym B

Aug 30, 2020

Very good basic linear algebra course which explains intuition behind concepts like eigen values/eigen vectors, matrix as a geometric transformation.

By George d V C N

Jul 11, 2020

I really good course for someone who never had the opportunity to study linear algebra and already have passed for some concepts in machine learning!

By Janaki R

Jun 4, 2020

Great intro to the subject, at a level that was just right for me (challenging but not overwhelming). Very friendly, well-produced videos. Thank you!

By Rushil D

Sep 3, 2018

Fantastic recap on linear algebra concepts.

The focus on intuitive understanding is a pleasure and far more engaging than more traditional approaches.

By Muhammad I A G

Feb 26, 2021

Really great, well explained, and detail course about linear algebra. Really hope that this knowledge will help me to my future studies and project.

By Md M M I

Jan 23, 2021

Coursera is my favorite place to learn. When I feel I need to introduce myself with some enchanting topics, then simply register course on Coursera.

By Mirko M

Jul 19, 2020

Great course to build confidence and intuition in linear algebra. Not much focus on practical computations, but that' s not the scope of the course.

By Kirill K

Jan 26, 2021

Nice and quick recap of linear algebra if you had it in university several years ago. If you are total zero better find something more fundamental.

By Aman A

Oct 9, 2019

One of the most concise and yet complete courses on Linear algebra in the light of its practical application in the real world and machine learning

By Muhammad H T

Jul 7, 2020

Awesome course by Imperial College London. Core concept fo macine learning, data science, and both instructors teach in with their depth knowledge

By Mohammad A M

Oct 22, 2019

This course gives you an in-depth understanding of Linear Algebra concepts that are momentous for Machine Learning, so DO NOT hesitate to take it.

By Hritik K S

Dec 8, 2018

I learned the best visualisation of linear algebra's concepts. Nothing is better that understanding the concepts and how the things are happening.

By Amod A

Jun 11, 2018

Extremely Helpful.Every Machine Learning Aspirant should complete this course to get the basics right! Instructors and Course Content are perfect.

By Andrew

May 12, 2020

Combined with 3Blue1Brown this course is gorgeous. It would be nice, though, to have more details covered, explanations and non-trivial examples.

By Nguyễn Đ A T

Dec 26, 2020

I thinks course its very helpful for machine learning but Its so hard to present code in the quiz

Student might be bored about that . Thanks you

By Rodrigo H d F

Jun 11, 2020

Love this course! Quite didatic, illustrates how Linear Algebra and Machine Learning are connected. Teachers explain brilliantly. Fantastic one!

By Julian A M M

Jun 4, 2020

The teachers are quite good and the subjects of the course very interesting, I learned many new things and I feel that it is very useful for me.

By Donna D C

Apr 16, 2020

Excellent course for developing intuition for linear algebra, transformation matrices, basis changes, and eigenvalue and eigenvector operations.

By Deleted A

Apr 12, 2020

The instructors explained everything really well. I took Linear Algebra in university and could not understand things as well as in this course!

By yifei l

Dec 21, 2019

Great linear algebra part, compare to regular linear algebra class. This class focues more on intuitive and practice. I really enjoy this class.

By ChaoLin

Oct 25, 2018

only the homework is not so friendly to the people who do not use python often, and the other is so good, especially about the teachers, thanks!