Back to Mathematics for Machine Learning: PCA

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2,835 ratings

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....

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.

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.

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By Farhan F

•Mar 26, 2022

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

By Haofei M

•Apr 22, 2020

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

By Deepak T

•Apr 17, 2020

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

By Mohammad A M

•Nov 14, 2019

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

By Alfonso J

•Oct 20, 2019

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

By MD K A

•Aug 8, 2020

Algebra, Calculus and PCA

These are all excellent, if you have mathematics knowledge

By Arijit B

•Nov 5, 2019

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

By Pascal U E

•May 25, 2018

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

By Greg E

•Jul 27, 2019

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

By Faruk Y

•Sep 22, 2019

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

By Rodrigo S

•Feb 22, 2022

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

By Sanjay B

•Dec 30, 2020

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

By Lia L

•May 22, 2019

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

By Pritam C

•Sep 22, 2020

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

By Nero

•Aug 5, 2022

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

By Roshan C

•Nov 23, 2019

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

By Hanif A

•Mar 1, 2021

I think there must be correction for the pca lab, the testing code is error

By Pramod H K

•Aug 7, 2020

The highly mathematical perspective of PCA with greater conceptualization.

By Rishabh A

•Jun 17, 2019

We need more elaborate explanation at few tricky places during the course.

By Aman M

•Jul 1, 2020

good content but assignment quality and maintenance should be rechecked

By Seelam S

•Jul 25, 2020

Good Course to get knowledge of Maths required for Machine Learning! ☺

By Sanchayan D

•Jun 7, 2020

Good Introduction to understanding the principal component analysis

By Sekhar K

•Aug 18, 2021

Excellent course! Really enjoyed it. All professors were great!!

By Benjamin C

•Jan 28, 2020

Excellent course regarding both theoritical and practical sides.

By Shahriyar R

•Sep 14, 2019

The hardest one but still useful, very informative neat concepts

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