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

4.0
stars
2,214 ratings
551 reviews

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 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.

NS
Jun 18, 2020

Relatively tougher than previous two courses in the specialization. I'd suggest giving more time and being patient in pursuit of completing this course and understanding the concepts involved.

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326 - 350 of 548 Reviews for Mathematics for Machine Learning: PCA

By Andrew D

Jun 2, 2019

Very difficult course, make sure to do the prereq courses first and understand everything from those courses.

By Neelam J U

Sep 23, 2020

The programming assignments were quite challenging. Some part of the course can discuss this aspect as well.

By Paulo N A J

Aug 18, 2020

It is a good course with hard programming, but the assignments could be improved. The forum helps a lot.

By Ibon U E

Jan 7, 2020

The derivations of some concepts have been more vague compared to other courses in this specialization.

By Max W

Apr 19, 2020

Very challenging, could have used a few more videos to really explain or give a few more examples

By Abhishek T

Apr 12, 2020

The structure could have been better. Some of the weeks were too crowded as compared to others

By Phuong A N

Aug 7, 2020

very difficult course. But I hope that it will be useful fore my machine learning studying

By kerryliu

Jul 30, 2018

still have room for improvement since lots of stuffs can be discussed more in detail.

By Ruan v S

Oct 13, 2019

Harder than expected, the content is good and is well worth the struggle!

By Xin W

Sep 6, 2019

This course is full of mathematical derivation, so it is kind of boring.

By Felipe T B

Aug 10, 2020

Computational exercises could have more support from the professors.

By Jiaxuan L

Jul 15, 2019

Overall a good course. Very limited introduction to Python though.

By Chow K M

Jul 28, 2020

Quite challenging. Need to keep notes for programming assignment.

By Lafite

Feb 4, 2019

编程练习的质量不够高,不管是编程练习本身的代码逻辑、注释、练习的质量还是在答疑区课程组的答疑都不能尽如人意,对于编程练习并不很满意

By Attili S

Aug 19, 2020

Great course! It could have elaborated more in the week 4 PCA

By Ashok B B

Feb 6, 2020

Course was challenging , but learned the maths behind PCA,

By Cesar A P C J

Dec 23, 2018

Good content, just need to fix the assignments' platform.

By Dave D

May 30, 2020

This course was a fair overview of a very complex topic.

By ADITYA K

May 13, 2020

It is very informative and hands-on based Course for PCA

By Md. S B S

May 4, 2020

Not as good as the other two courses..but interesting!

By Sharon P

Sep 24, 2018

Mathematically challenging, but satisfying in the end.

By Paulo Y C

Feb 11, 2019

great material but explanation are a little bit messy

By taeha k

Jul 27, 2019

Good but slightly less deeper than the other two

By Eddery L

May 23, 2019

The instructor is great. HW setup sucks though.

By Manish C

May 6, 2020

Best course for machine learning enthusiast