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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
12,267 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 9, 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

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.

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1751 - 1775 of 2,432 Reviews for Mathematics for Machine Learning: Linear Algebra

By Aditya S

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Dec 6, 2019

awesome

By Bhavya G

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Jul 20, 2019

Amazing

By Sheikh N I

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Jul 2, 2018

Thanks!

By Julio M

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Sep 23, 2024

Great!

By Indriana N

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Mar 22, 2023

Amzing

By RAHMITA D K

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Mar 17, 2023

Mantep

By Hoang D

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Dec 27, 2021

useful

By mochammad g r

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Mar 3, 2021

Thanks

By 龚古铮

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Feb 2, 2021

Great!

By Thanh L P

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Aug 6, 2020

Great!

By Rehab A

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Jul 4, 2020

thanks

By Flt L G R

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May 26, 2020

THANKS

By Shijing C

•

Mar 27, 2019

useful

By János G

•

Feb 10, 2019

Superb

By Muhammad N I

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Mar 25, 2022

great

By Syeka B P

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Mar 21, 2022

great

By Lisa A

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Mar 2, 2021

Great

By Bojia S

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Jan 27, 2021

nice！

By Olzhas E

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Dec 9, 2020

хз хз

By Prabal G

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Oct 13, 2020

great

By Md. R Q S

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Aug 20, 2020

great

By Syed s A

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Jul 13, 2020

Nice!

By shobit G

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Nov 7, 2018

good!

By Stephen

•

Sep 7, 2023

nice

By Piriyadarshini K

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May 24, 2023

good