Back to Mathematics for Machine Learning: PCA

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2,669 ratings

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671 reviews

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 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 Roshan C

•Nov 23, 2019

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

By Hanif Y A P

•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

By J G

•May 12, 2018

This is a good course, you learn about the foundations of PCA.

By Opas S

•Jul 15, 2020

Great course for improve math skilled and improve basic to ML

By Isaac M M

•Aug 9, 2020

A bit more difficult than previous ones but it is worth it

By Phani B R P

•Jun 1, 2020

Very good course and extremely challenging, especially PCA

By Anh V

•Nov 15, 2020

Very detailed explanation and mathematics underlying PCA!

By Md. A A M

•Aug 24, 2020

Great Course. Everyone should take this course. Thanks.

By Harish S

•Nov 24, 2019

This was a difficult course but still very informative.

By Oleg B

•Jan 6, 2019

Excellent focus on important topics that lead up to PCA

By Kaustubh S

•Nov 29, 2020

Very tough course but got a good sense of what PCA is

By Prateek S

•Jul 14, 2020

best course and important to study with concentration

By Lahiru D

•Sep 16, 2019

Great course. Assignments are tough and challenging.

By Archana D

•Mar 6, 2020

Brilliant work, references and formulas aided a lot

By Tich M

•Jan 18, 2019

good course, rigorous proof and practical exercises

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