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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
12,311 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 26, 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 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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1776 - 1800 of 2,437 Reviews for Mathematics for Machine Learning: Linear Algebra

By shobit G

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Nov 7, 2018

good!

By Stephen

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Sep 7, 2023

nice

By Piriyadarshini K

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May 24, 2023

good

By Muhammad K M

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Mar 31, 2023

good

By Muhammad J

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Mar 28, 2023

Good

By Angger M R

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Mar 16, 2023

good

By Fitrah S

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Mar 16, 2023

cool

By Kaushal A

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Jan 27, 2023

Good

By Elkin A V S

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Apr 14, 2022

good

By Doni S

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Mar 27, 2022

Good

By Quế A

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Jul 24, 2021

nice

By 안병수

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Jul 16, 2021

good

By 지홍근

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Apr 2, 2021

good

By Alivia Z

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Mar 18, 2021

good

By Habib B K

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Mar 11, 2021

Nice

By Jatu K R

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Mar 10, 2021

nice

By Ahmad H N

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Mar 1, 2021

Good

By Hana B

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Feb 28, 2021

good

By Indah D S

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Feb 26, 2021

good

By Layyinatus S

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Feb 24, 2021

wow!

By Felix C

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Feb 23, 2021

good

By Merey O

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Dec 11, 2020

nice

By Yiya W

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Dec 1, 2020

good

By RAGHUVEER S D

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Jul 25, 2020

good

By Chow K M

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Jul 24, 2020

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