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

4.0
stars
2,198 ratings
548 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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501 - 525 of 543 Reviews for Mathematics for Machine Learning: PCA

By Matt C

Jul 1, 2018

I was expecting to learn a lot in this course. I did not. The lectures don't really explain much at all and then you're thrown a quizzes and assignments that do not match what was in the actual lectures. The rest of the specialization was great but this course falls of the other two.The explanations in the videos are very poor. Really disappointed.

By Cynthia M

Jun 9, 2018

The course is mathematics for Machine Learning. Yet, they require that you are proficient in python. I understand the mathematics. However, no one will answer my questions on the python we are suppose to code. I passed both of the previous courses. I've taken and passed Statistics with python on edX. I've very disappointed in this course.

By Steve

Sep 5, 2020

Very sketchy presentation of complex material. Each lecture averaged around 5-6 minutes when they should have been 15-20 minutes. As a result the instructor glossed over the material without adequate explanations and derivations. And no one at Imperial College seems to be responding to recent posts in the discussion forums.

By Kannan S

Apr 11, 2018

There are no numerical examples as the course progresses. The instructor does everything algebraically. As a result I was not able appreciate the practical use of PCA. Later on I saw there are very nice videos in Youtube that illustrate the concept more lucidly using numerical examples. I am disappointed.

By Gassysoil

Oct 13, 2019

Marc Peter Deisenroth jumps too much at the important computation steps. Some steps might be simple to him, but it could be very misleading to students.

Often times, he will just throw out some equations without letting the student know what exactly we are trying to achieve.

By Rob E

Aug 11, 2020

Intentionally obtuse. No effort whatsoever is given to helping people learn. The instructors don't answer questions and they admittedly make their lectures hard to understand.

I only took this because there were no other courses on available at the time.

By Kristina S

Aug 24, 2018

One of the worst online courses I have had. Inconsistent teaching, relaying on students having previous knowledge about Python and rads (where the heck did that come from?), failing to convey what and where this is practically used for.

By Oliver K

Feb 21, 2020

PCA was my main interest in this specialization, and it felt very rushed and lazy (i.e. important explanations are fully missing, or just done via pdf from a book). I used *a lot* of Khan Academy to understand what's going on.

By Kumar S

Aug 11, 2020

I would give ONE STAR because the instructor of this course was worst. He don't know the teaching and concepts too. He seems to be so low energetic instructor I have ever seen. A very bad experience after taking this course.

By Musabbir H S

Jan 31, 2020

I don't know if this course has been deliberately made hard to understand or I was lacking something. Lectures were pretty useless to me. Coding exercises were not clearly defined. I felt utterly frustrated at times.

By Ashlee H

Nov 26, 2019

You'll likely catch on pretty early that this course will mostly expects you to learn the content elsewhere. You're paying for mostly just for assignments and quizzes which there are far more of than video lectures.

By Ed W

Nov 25, 2019

The lectures gave incomplete information for the understanding of the material and the homework assignments. Wish this course was stretched to be a 10 week course so that we can all thoroughly learn the material.

By Christiano d S

Aug 10, 2020

The lessons are not clear and if one wants to learn and understand what is going on with the math/algebra, has to study with other resources, because the videos of this course just throw up info´s on screen.

By Kimberely C

Dec 27, 2019

Definitely, not for beginners. Just as bad as the last one. They need to have more examples, which walk you through the ones like they give you on the homework as well as an example of how to do Python.

By Gurrapu N

Apr 9, 2020

There is hardly any co-relation between videos and assignments, while the lectures were at high school level but the assignments were at graduate level. It is high time to revise the course contents.

By Marcin

Aug 19, 2018

By far the worst online course that I've ever done. Assignments require a lot of experience in Python, which is not communicated upfront. At the same time, staff doesn't provide any actual support.

By Danielius K

Sep 24, 2019

You will spend most of your time lost.

Quizes are not clear and ill-prepared.

You will need to spend a lot of time looking for material outside of the course to actually make progress.

By Saransh G

Apr 28, 2020

1. Not intuitive like first two programs

2. The assignments sometimes jumped concepts and were not cohesive

3. The in-lecture problems seemed rushed through

By Tai J Y

Nov 16, 2019

This course is not like other two, which explain much clearly. When I do the practice quiz and coding, I resort to find other help on the Internet.

By Vibhutesh K S

May 17, 2019

This course is really bad and extremely hard to follow. Previous two courses were executed very well, teaching quality in this is poor.

By Alejandro T R

Aug 2, 2020

Worst of the three courses. I learned much more on the internet because of the lack of examples or explanation. Just not worth it.

By Ananya G

Dec 28, 2019

I did not register in this course to have some person read out the textbooks or dictate the derivations in the lecture videos.

By Michael K

Oct 18, 2020

Lowest rating as the third course was absolutely poor. Low quality and in some way non-existent instruction.

By Nithin K

Jun 5, 2018

Too conceptual and theoretical making it difficult to understand. Examples would have helped a lot.