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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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251 - 275 of 786 Reviews for Mathematics for Machine Learning: PCA

By Aishik R

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Jan 18, 2020

Excellent and to-the-point explanations, useful assignments to make the concepts etched in memory

By Haoquan F

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Feb 13, 2022

It's overall wonderful but the week 4's programming assignment really struggled and confused me.

By KAMASANI V R

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Jun 20, 2020

This course helped me in getting a deeper knowledge on Principal Component Analysis. Thank You.

By Wei X

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Oct 16, 2018

concise and to the point. Might want to introduce a bit the technique of Lagrangin multiplier

By Fab V

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Jul 31, 2022

A fascinating course letting people explore the beauties of Mathematics and Machine Learning

By Leonardo H T S

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May 3, 2021

This was an amazing course, I really enjoyed it and learn a lot!

Thank you so much, greetings

By Wahyu N A

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Mar 27, 2021

I'm struggle with assigments of week 4 about implementing PCA. But, yeaah finally i got this

By Mayank

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Dec 3, 2020

This course cleared so many concepts and enabled me to further master the subject on my own.

By Ripple S

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Mar 18, 2020

I learnt a lot from this course and now I think I am much more familiar with this algorithm.

By Farhan F

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Mar 27, 2022

This is very very very very very challengging, but i can do it because i try try and try

By Haofei M

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Apr 23, 2020

extremely informative and really help me understand the basic math in Machine learning

By deepak t

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Apr 17, 2020

Course was challenging, so does the math. It was a very excellent learning experience!

By Mohammad A M

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Nov 14, 2019

This course is also so helpful, and the lecturer is so predominant on what he taught.

By Alfonso J

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Oct 20, 2019

Truly hardcore course if your are a noob in reduced order modelling. Very challenging

By MD K A

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Aug 8, 2020

Algebra, Calculus and PCA

These are all excellent, if you have mathematics knowledge

By Arijit B

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Nov 5, 2019

Excellent course and extremely difficult one to grasp at one go. Regards Arijit Bose

By Pascal U E

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May 26, 2018

Very hard to follow, but you need to do it to understand machine learning very well.

By Greg E

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Jul 27, 2019

I have thoroughly enjoyed every course of this specialization. Thank you very much.

By Faruk Y

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Sep 22, 2019

Lectures and programming assignments were selected nicely to teach the math of PCA

By Rodrigo S

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Feb 22, 2022

Amazing course, really challenging tho, however, material lerned is very useful.

By Sanjay B

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Dec 30, 2020

Excellent program, helped get to understand features of Python programming fast

By Lia L

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May 22, 2019

This was really difficoult, but I'm so proud for the completion of the course.

By Pritam C

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Sep 22, 2020

It was an intense Math Class with a piece of new knowledge about PCA...Thanks

By Nero

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Aug 5, 2022

The instructor is doing a great job in explaining the mathematics behind PCA

By Roshan C

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Nov 23, 2019

the course was very much intuitive and helpful to grasp the knowledge of PCA