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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

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.

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.

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326 - 350 of 786 Reviews for Mathematics for Machine Learning: PCA

By Jyothula S K

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May 18, 2020

Very Good Course to Learn about PCA

By Thierry P

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Apr 21, 2022

good understanding of pca insight

By Carlos S

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Jun 12, 2018

What you need to understand PCA!!!

By 祈璃

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Jul 9, 2021

This module is quite challenging!

By Dina B

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Aug 8, 2020

Nice course - informative and fun

By saketh b

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Aug 10, 2020

The instructor did a great job!

By Sukrut B

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Oct 19, 2020

Try to make it little bit easy

By Javas A B Y P

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Mar 28, 2021

Alhamdulillah, this is great!

By Israel d S R d A

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Jun 6, 2020

Great course very recommended

By Muhammad T

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Mar 2, 2021

haha good course i completed

By Jonah L

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Dec 7, 2020

It's hard but it's worth it!

By Gautham T

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Jun 16, 2019

excellent course by imperial

By Ankur A

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May 15, 2020

Tough course, learnt a lot.

By Imran S

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Dec 20, 2018

Great Coverage of the Topic

By Ajay S

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Feb 20, 2021

Great course for every one

By Felix G S S

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Mar 27, 2021

Wow, it is so challenging

By Ricardo C V

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Dec 25, 2019

Challenging but Excellent

By CHAITANYA V

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Jul 17, 2020

Excellent course content

By Mayank K

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Jul 2, 2020

This course is very good

By Nihal T

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Jul 13, 2022

Amazing Specialization!

By Michael M

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Aug 3, 2021

I strongly recommend it

By Subhodip P

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Dec 15, 2020

Awesome course loved it

By Pranav N

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Aug 25, 2020

Amazing overall course

By iorilu

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Jun 4, 2021

intuitive and helpful

By Gazi J H

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Oct 16, 2020

Thank you very much.