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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
11,956 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

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.

NS

Dec 22, 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.

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1051 - 1075 of 2,368 Reviews for Mathematics for Machine Learning: Linear Algebra

By Pierre C D M

Mar 24, 2020

Very good very clear. Begineers will definitively have a take out.

By Shilpa S C

Feb 29, 2020

The assignments were hard ,but learned good amount of information.

By Julio V E

May 21, 2018

Excellent course, with a great team of well-motivated instructors.

By Alessio T

Sep 18, 2022

Very clear explanations of very important and interesting topics

By Berlian P R H

Mar 12, 2021

this course is improve me basic of mathematics. thank you so much

By George P

Sep 10, 2020

Demanding but worth it. You have got to mirror the bear to see...

By MICHAEL P A P

Aug 3, 2020

Si colocan subtitulo en español seria fantástico.

Excelente curso.

By Mukunda M N

Jan 25, 2020

Intuitive explanations rather than jargons, very enjoyable course

By manoranjan s

Nov 5, 2019

I really enjoyed this course. This was a good refresher for my LA

By Alexander v d P

May 22, 2018

Very clear quick browse through some concepts from linear algebra

By YW

Apr 11, 2018

excellent course for freshen-up linear algebra, highly recommend!

By Daniel M

Feb 14, 2021

Fundamental to understand the foundations of the Linear Algebra.

By Akshay K

Feb 12, 2020

Best course to start off with for people stepping into ML field.

By Ravindu T

Oct 3, 2019

The course is very informative and really interesting to listen.

By Avi M

Aug 14, 2019

Good for developing linear algebra intuition and helps visualize

By Eduardo Z R

Jan 29, 2022

Nice and complete course with the essential knowledge to apply.

By Alexandre G

Jun 3, 2021

A clear and informative course that re-cindle my love for maths

By premjeetprasad

Aug 10, 2020

Excellent amount of knowledge presented in a simpler visual way

By 李赞

Apr 3, 2020

it's quiet short but contains most of the important imformation

By Wenwen L

Aug 20, 2019

Hope this module can covers more about dimension reduction etc.

By Hao G

Jan 27, 2021

Very good course materials, but the marking system is annoying

By Ashok M

Aug 12, 2020

Must watched Course for Machine learning and all Mathematician

By Vikas K P

Jun 29, 2020

good course to understand the mathematics for machine learning

By Danielius K

May 23, 2018

An amazing introduction to a crucial part of machine learning!

By AP P

Jul 24, 2023

Very good for beginners interested in artificial intelligence