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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
12,286 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

GB

Aug 16, 2020

The instruction was good throughout, but I would urge fellow students to take the time to work through the problems as suggested. Also, the eigen- stuff is quite tricky and can fool you. Be careful.

MG

May 30, 2020

A great course covering key aspects of Linear Algebra with the lecturers giving a good intuition about what's going on with the subjects.(PS. I loved the sense of humor of Prof.Dye it was really fun!)

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By Piriyadarshini K

May 24, 2023

good

By Muhammad K M

Mar 31, 2023

good

By Muhammad J

Mar 28, 2023

Good

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Mar 16, 2023

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By Fitrah S

Mar 16, 2023

cool

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Jan 27, 2023

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Apr 14, 2022

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Mar 27, 2022

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Jul 24, 2021

nice

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Jul 15, 2021

good

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Apr 1, 2021

good

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Mar 17, 2021

good

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Mar 10, 2021

Nice

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Mar 10, 2021

nice

By Ahmad H N

Mar 1, 2021

Good

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Feb 28, 2021

good

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Feb 25, 2021

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Feb 24, 2021

wow!

By Felix C

Feb 23, 2021

good

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Dec 11, 2020

nice

By Yiya W

Nov 30, 2020

good

By RAGHUVEER S D

Jul 25, 2020

good

By Chow K M

Jul 24, 2020

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By Jay

Jul 22, 2020

good

By moksha m

Jul 16, 2020

good