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学生对 Imperial College London 提供的 Mathematics for Machine Learning: PCA 的评价和反馈

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3,155 个评分

课程概述

This intermediate-level course introduces the mathematical foundations to derive Principal Component Analysis (PCA), a fundamental dimensionality reduction technique. We'll cover some basic statistics of data sets, such as mean values and variances, we'll compute distances and angles between vectors using inner products and derive orthogonal projections of data onto lower-dimensional subspaces. Using all these tools, we'll then derive PCA as a method that minimizes the average squared reconstruction error between data points and their reconstruction. At the end of this course, you'll be familiar with important mathematical concepts and you can implement PCA all by yourself. If you’re struggling, you'll find a set of jupyter notebooks that will allow you to explore properties of the techniques and walk you through what you need to do to get on track. If you are already an expert, this course may refresh some of your knowledge. The lectures, examples and exercises require: 1. Some ability of abstract thinking 2. Good background in linear algebra (e.g., matrix and vector algebra, linear independence, basis) 3. Basic background in multivariate calculus (e.g., partial derivatives, basic optimization) 4. Basic knowledge in python programming and numpy Disclaimer: This course is substantially more abstract and requires more programming than the other two courses of the specialization. However, this type of abstract thinking, algebraic manipulation and programming is necessary if you want to understand and develop machine learning algorithms....

热门审阅

JS

Jul 16, 2018

This is one hell of an inspiring course that demystified the difficult concepts and math behind PCA. Excellent instructors in imparting the these knowledge with easy-to-understand illustrations.

WS

Jul 6, 2021

Now i feel confident about pursuing machine learning courses in the future as I have learned most of the mathematics which will be helpful in building the base for machine learning, data science.

筛选依据：

351 - Mathematics for Machine Learning: PCA 的 375 个评论（共 790 个）

创建者 iorilu

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Jun 3, 2021

intuitive and helpful

创建者 Gazi J H

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Oct 16, 2020

Thank you very much.

创建者 Yasser Z S E

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May 26, 2020

Thank you very match

创建者 wonseok k

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Mar 3, 2020

hard but good course

创建者 K F

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Sep 15, 2019

I had big fun of PCA

创建者 Rajkumar R

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Jun 20, 2020

I enjoyed learning.

创建者 Jason K

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Jul 23, 2021

Excellent Course !

创建者 Omar Y B L

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Jul 15, 2020

Cruel pero justo!!

创建者 N'guessan L R G

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Apr 14, 2020

Amazing Course!!!!

创建者 Dominik B

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Feb 17, 2020

Great instructor!

创建者 Sujeet B

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Jul 21, 2019

Tough, but great!

创建者 Jitender S V

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Jul 25, 2018

AWESOME!!!!!!!!!!

创建者 Shanxue J

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May 23, 2018

Truly exceptional

创建者 Deepanshu T

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Jan 30, 2023

Awesome Learning

创建者 Sabrina M U

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Mar 27, 2021

alhamdulillah :)

创建者 Habib B K

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Mar 13, 2021

Nice Chalengging

创建者 Lintao D

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Sep 23, 2019

Very Good Course

创建者 Spandan G

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Jul 27, 2024

Ultimate course

创建者 Divyansh K

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Nov 29, 2020

It was so tough

创建者 Firli A R

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Mar 26, 2022

amazing course

创建者 EDWARD J R

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Nov 29, 2020

Amazing course

创建者 Shounak D

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Sep 15, 2018

Great course !

创建者 Sabeur M

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Dec 19, 2023

Great Courses

创建者 Andrey

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Sep 17, 2018

Great course!

创建者 Samresh

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Aug 10, 2019

Nice Course.