Back to Mathematics for Machine Learning: Linear Algebra

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10,413 ratings

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2,083 reviews

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....

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.

CS

Mar 31, 2018

Amazing course, great instructors. The amount of working linear algebra knowledge you get from this single course is substantial. It has already helped solidify my learning in other ML and AI courses.

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By Alexander D K

•Aug 21, 2019

Fairly good introductory course but not a substitution for a proper LA course for ML purposes.

By MIGUEL A G H

•Dec 27, 2020

Very usefull to deep in the mathematical foundations of machine learning. Very recommendable.

By Andrew X

•Nov 2, 2020

In week 5, some practice questions seems a little irrelevant to the key mathematical concepts

By Aditya G

•Sep 2, 2019

The course is really nice. A bit of programming experience is needed to complete this course.

By Nishant A

•Jun 4, 2018

Brilliant brush up course. Could have had a little more about eigen vectors and eigen values

By bowman

•Jul 24, 2020

it's an execlent course, but week5 should be extend to make it clear and easy to understand

By Utkarsh L

•May 15, 2020

Some video lectures should be there which will give some ideas about how to do programming.

By George P

•Apr 12, 2020

Excellent course as a refresher if you've studied Physics and need to recover the content

By Peeyush S K

•Nov 20, 2021

Teaching Style and the Teaching Aids were very effective. Personally I liked the course.

By Elnur M

•Apr 8, 2020

I think it would be better if you add Singular Value Decomposition concept into syllabus

By Hayder M A

•Apr 25, 2020

Very useful materials and the instructors are very good and make it easy to understand.

By parikshit s

•Feb 16, 2020

Really Good course, learnt a lot of things, just wanted this course to be in more depth

By Antoine P

•Jan 20, 2021

Really intersting. Could be a bit difficult for people without mathematical background

By akhil

•May 31, 2020

Sam part wasn't so impressive. Really loved the way David has gone through the course.

By Zhejian C

•Jan 20, 2020

Teach good intuition and good explanations but maybe a bit shallow, good for beginners

By Andrew K

•Feb 17, 2019

great visual explanations of concepts, but the course could have been more informative

By Vinayak k

•Jun 7, 2020

Very good insight of linear algebra. It give different prospective of linear algebra.

By Michał K

•Nov 29, 2019

Good course, advise to take it, though sometimes not everything explained thoroughly!

By Max W

•Mar 2, 2020

excellent approach to linear algebra, high quality and carefully thought out lessons

By Robin S

•Feb 17, 2020

Very nice course. A good math overview with a balance between details and practice.

By Kyle B

•Sep 23, 2020

Good course, Its a very good basis to build a math foundation for machine learning

By Hamza K

•Nov 30, 2019

Instructor should give more example related to Data Science and Machine Learning.

By Debzani M

•Apr 29, 2020

An organized course, great for developing the imagination of mathematics and fun.

By Deleted A

•Jul 19, 2019

Really intuitive course on matrix algebra with very clear geometric explanations.

By Secret S L

•Sep 27, 2021

Good overview. I definitely had to go to outside material for the Row Reduction.

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