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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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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.

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376 - Mathematics for Machine Learning: PCA 的 400 个评论（共 791 个）

创建者 Snehal P

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Sep 11, 2020

Nice Course

创建者 Manikant R

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Jun 8, 2020

Best course

创建者 Salah T

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Apr 26, 2020

Many thanks

创建者 Artur

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Feb 29, 2020

good course

创建者 Afdoni P S

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Mar 28, 2023

yooooyooo

创建者 Bintang F E

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Mar 28, 2021

awesome!!

创建者 Muhammad T R T P

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Mar 28, 2021

good one!

创建者 Andreanov R

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Mar 15, 2021

very hard

创建者 miguel s

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Sep 20, 2020

very well

创建者 Mohamed H

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Aug 10, 2019

fantastic

创建者 Karthik

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May 3, 2018

RRhis cl

创建者 Juan C F G

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Aug 4, 2024

Awesome

创建者 Sudarshan J

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Feb 12, 2023

great !

创建者 Levina A

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Mar 27, 2021

So cool

创建者 alfatoni n

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Mar 12, 2021

Finally

创建者 Akash G

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Mar 20, 2019

awesome

创建者 Bálint - H F

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Mar 20, 2019

Great !

创建者 RAHMITA D K

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Mar 29, 2023

Mantep

创建者 Sean F

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Jun 22, 2021

Tough.

创建者 liuye y

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Mar 3, 2025

good!

创建者 Ahmad H A

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Mar 27, 2022

great

创建者 Insyiraah O A

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Mar 26, 2022

GREAT

创建者 Mellania P S

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Mar 23, 2021

great

创建者 Indah D S

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Mar 9, 2021

great