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Mathematics for Machine Learning: Linear Algebra

Coursera · Imperial College London · 2 HN comments

HN Academy has aggregated all Hacker News stories and comments that mention Coursera's "Mathematics for Machine Learning: Linear Algebra" from Imperial College London.
Course Description

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.

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This course is offered by Imperial College London on the Coursera platform.
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Hacker News Stories and Comments

All the comments and stories posted to Hacker News that reference this url.
I've just finished the coursera's Mathematics for Machine Learning: Linear Algebra ( and I'd say its very good for beginners
A bit weird to add a negative review, but here goes:

Is _not_ a good introduction. The instructors are all over the damn place, and you will spend much of your time finding better explanations from other sources. Wish I hadn't started with this. On the plus side, you will get a certificate at the end.

Indeed weird, because the course you mentioned is actually excellent. However, it was designed for people who had (somehow) already seen the subjects in an abstract and unapplied setting (such as a math class at uni). They refresh or refocus the subjects with a geometric intuition and with some concrete applications in mind; which I found quite useful and beautiful. This class is more like a more developed version of 3b1b videos on LA.
It's funny, because as I was reading your comment, I was thinking of 3b1b. He's doing great work by visualizing abstract concepts, but I think what he does mainly helps people who have already gone through the material. If it's your first time encountering the topic, you'll likely feel lost or not see the point.

What 3b1b does still brings a lot of value, so I don't want to take away anything from his work.

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