返回到 Mathematics for Machine Learning: Linear Algebra

4.6

1,712 个评分

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301 个审阅

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....

创建者 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.

创建者 CS

•Apr 01, 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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298 个审阅

创建者 Hritik Kumar Sharma

•Dec 08, 2018

I learned the best visualisation of linear algebra's concepts. Nothing is better that understanding the concepts and how the things are happening.

创建者 Jishnu Bhattacharya

•Dec 07, 2018

This is a very good course - less of symbols and more of intuition,which is more important in applications. Profs are excellent communicators - even if you zero knowledge of the subject - you will get 100% of it...

创建者 Samuel Zhao

•Dec 07, 2018

Amazing course!

创建者 Dan Gomulkin

•Dec 07, 2018

I very friendly introduction to linear algebra that makes you fully comfortable with it.

创建者 Kyle Welch

•Dec 06, 2018

Excellent course. It's very practical - focuses on building your intuition of core concepts and applying those concepts through simple programming exercises.

创建者 Angelo C0d3r

•Dec 05, 2018

Nice refresher! Excellent instructors! Not recommended as a first Linear Algebra course though. I would go for MIT OpenCourseware first.

创建者 Maximilian Pfister

•Dec 05, 2018

Some exercises are completely incoherent to the preceding videos, which makes it very difficult to solve them. very frustrating

创建者 Zhuocheng Yu

•Dec 02, 2018

The programming grading system doesn't work well, but the course is great anyway

创建者 Serge H kamga

•Nov 25, 2018

I love the stuff that I learned: the usefulness of eigenvalues and eigenvectors, coding pagerank algorithm, gram Schmidt to create orthonormal basis, ...

创建者 Jinwoong Kim

•Nov 24, 2018

nice intro to the linear algebra world and relevant code