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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
12,186 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

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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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

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Jul 16, 2021

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Apr 2, 2021

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Mar 10, 2021

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Mar 10, 2021

nice

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Mar 1, 2021

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Feb 28, 2021

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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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Nov 30, 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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By Luke

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Jul 22, 2020

good

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Jul 17, 2020

good

By Akshatha Y

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Jul 16, 2020

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Jul 15, 2020

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By BALAJI.V

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Jul 13, 2020

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By RAMÍREZ S C A

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Jun 29, 2020

Nice

By Nalongsone D

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Jun 16, 2020

good

By Vinish R

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May 12, 2020

nice