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Learner Reviews & Feedback for Mathematics for Machine Learning: PCA by Imperial College London

4.0
stars
3,144 ratings

About the Course

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....

Top reviews

JS

Jul 17, 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 7, 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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351 - 375 of 786 Reviews for Mathematics for Machine Learning: PCA

By Yasser Z S E

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May 26, 2020

Thank you very match

By wonseok k

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Mar 3, 2020

hard but good course

By K F

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Sep 15, 2019

I had big fun of PCA

By Rajkumar R

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Jun 20, 2020

I enjoyed learning.

By Jason K

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Jul 24, 2021

Excellent Course !

By Omar Y B L

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Jul 15, 2020

Cruel pero justo!!

By N'guessan L R G

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Apr 15, 2020

Amazing Course!!!!

By Dominik B

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Feb 17, 2020

Great instructor!

By Sujeet B

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Jul 21, 2019

Tough, but great!

By Jitender S V

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Jul 25, 2018

AWESOME!!!!!!!!!!

By Shanxue J

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May 23, 2018

Truly exceptional

By Deepanshu T

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Jan 30, 2023

Awesome Learning

By Sabrina M U

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Mar 27, 2021

alhamdulillah :)

By Habib B K

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Mar 14, 2021

Nice Chalengging

By Lintao D

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Sep 24, 2019

Very Good Course

By Spandan G

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Jul 27, 2024

Ultimate course

By Divyansh K

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Nov 30, 2020

It was so tough

By Firli A R

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Mar 27, 2022

amazing course

By EDWARD J R

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Nov 29, 2020

Amazing course

By Shounak D

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Sep 15, 2018

Great course !

By Sabeur M

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Dec 19, 2023

Great Courses

By Andrey

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Sep 17, 2018

Great course!

By Samresh

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Aug 10, 2019

Nice Course.

By David N

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Jul 24, 2019

Great course

By Snehal P

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Sep 11, 2020

Nice Course