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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
12,188 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

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

CS

Mar 31, 2018

Amazing course, great instructors. The amount of working linear algebra knowledge you get from this single course is substantial. It has already helped solidify my learning in other ML and AI courses.

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2126 - 2150 of 2,416 Reviews for Mathematics for Machine Learning: Linear Algebra

By Nugy

Feb 24, 2021

The eigen value and eigen vector courses are a bit hard to understand

By Kevin O

Feb 25, 2021

A good refresher with some really useful insights about eigenthings.

By KIRANKUMAR M

Jul 21, 2020

Its is the best course to know about matrices and their applications

By KURRA S S 2

Dec 26, 2022

It is so useful to me for getting the knowledge in machine learning

By Sharad K L

Mar 9, 2020

Exams were hard and most of the exams were source of the knowledge.

By JOSÉ M B D

Jan 25, 2020

excelente curso, me gustaría que se complementara con programación.

By Eduardo G R G

Feb 4, 2024

i would prefer less explanation on the methods and more examples

By Jihun Y

Jan 3, 2022

teaching essential, doesn't cover many topics, but well curated!

By Sai V P

Aug 14, 2020

Decent course. Wish things were explained in a more detailed way

By Ng Y Y

Jun 21, 2019

Good overview and introduction to key concepts of linear algebra

By Mohammed K A

Feb 12, 2022

need some use of visualisation in some topic like change basis

By fatima s

Jun 18, 2020

Wish it was a bit more spontaneous but overall great content!!

By Vincent C

Apr 18, 2024

Explanation is good, but there are mistakes in the lectures.

By Gautam K

Mar 7, 2019

Highly recommended course for beginners in Machine Learning.

By Deleted A

Jan 3, 2019

Good grounding in the fundamental mathematics needed for ML

By Alagu P P G

Jun 18, 2020

good start up for algebra enthusiasist.

a strong foundation

By Deleted A

Apr 23, 2020

I felt that lectures aren't enough to solve the exercises.

By celwang

Mar 23, 2020

good course ! but some of the formula should be more clear

By 谢迟

Jun 25, 2018

The core idea of eigenvalue and eigenvector is very good.

By Andini A M

Mar 12, 2021

I thought it was lacking in practice before the LAB test

By Pakpoom S

Aug 6, 2021

Good course but should dig more deeper in math concepts

By 张力

Feb 6, 2021

Inspired me how to look at matrix, but not deep enough

By Kirill P

Dec 19, 2023

Good for people who know the basics of linear algebra

By Alisa G

Apr 25, 2020

great teachers, very practical quizzes and examples!

By Monhanmod K

Oct 10, 2018

not bad, I feel the information is not enough for ML