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学生对 伦敦帝国学院 提供的 Mathematics for Machine Learning: Linear Algebra 的评价和反馈

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11,190 个评分

课程概述

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....

热门审阅

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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1 - Mathematics for Machine Learning: Linear Algebra 的 25 个评论(共 2,222 个)

创建者 Georg K

Sep 8, 2018

创建者 ATUL A

Mar 13, 2019

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Mar 15, 2019

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Mar 20, 2019

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Apr 23, 2019

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Apr 1, 2018

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Dec 23, 2018

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Oct 17, 2019

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Jan 13, 2019

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Nov 15, 2018

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Aug 26, 2018

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Apr 28, 2018

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Feb 4, 2019

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Feb 25, 2019

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Mar 9, 2019

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Sep 21, 2018

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Jan 21, 2019

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Sep 10, 2019

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Mar 25, 2019

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Nov 13, 2018

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May 28, 2019

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Jun 6, 2018

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Aug 1, 2019