Back to Mathematics for Machine Learning: PCA

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2,571 ratings

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639 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....

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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By Hannah Q

•Apr 26, 2021

This is the worst course among 3 courses in this math for machine learning specialization, but this is also the most important one as it comprises the other 2 courses. the homework is not well designed, the lecture is not taught enough to finish the homework. the last coding assignment has so many errors. and TA is never available, there are just a group of people tried really hard to help each other in the discussion forum, and please read the discussion forum every one is confused and suffering from your this bad course.

By Adarsh R K S

•Feb 21, 2021

The first two courses in the entire specialization were good. The PCA course was then suddenly so complicated and assumed significant matrix knowledge which was not taught in the previous courses. also, the course kept introducing concepts into the material without any explanation of where this came from and the why behind it. the lecturer needs to understand that most people taking this course are not mathematicians by profession and so we would have learnt better if the PCA was kept at a basic level.

By Srudeep K

•Apr 6, 2021

Alot of the material are to be referred, read and understood from sources outside of the course which is frustrating. There is lack of continuation from first two courses (Linear algebra & Multivariate calculus). At times, lecturer explains concepts without giving any background. Tests front run the course, meaning some questions you get in tests are taught in the video just after the test. I find better resources elsewhere online to understand PCA much better than wasting few days on this course.

By Hossameldein E

•Apr 9, 2021

The other Two courses are great, really great. But this one is a disaster.

Most of the the first 3 weeks i google the theory again to understand the problems in the quizzes.

The 4th week feels like something from a different course.

This videos are dull . a lot of time just reading the equations without trying to know what is it about in the real life.

please reconsider re-constructing this course. it's really sad that after the two great courses it ends up with this.

By Rameses

•Aug 18, 2020

This has to be one of most nightmarish, ugly, courses I have taken on the Coursera platform. Lousy, boring instructor, assignments that are so full of bugs that even the staff cannot resolve the issues. Add to that very low participation from the mentors and teaching staff in responding to student concerns and questions.

Hey Marc, teaching staff and Imperial College. Get your act together!!

IOW This course sucks big time! Take it at your own risk

By Indira P

•Mar 26, 2021

I'm sorry but it is hard to understand. My expectation before starting this course is I'll be able to understand mathematic in an easier and better way but this is too complex to understand. I think you need to simplify this or make the course in a more fun way. Other than that, the course give me so much knowledge and it was so fun to learn all of these even though it require most of my time

By Raghav G

•Jul 13, 2020

The course is very monotonic and boring and it is quite difficult to understand much of what the extremely mathematical terms that the instructor does. I am an M.Sc. Mathematics student and even I could not understand nor enjoy more than half of the course. I would strongly advise against taking this course, however the other two courses from this specialization are good and interesting.

By Deleted A

•Jul 31, 2019

Feedback for the assignments sucks! The discussion forums don't help. I have to submit the last assignment last 6 times until it work, and I still don't know why my previous versions didn't pass. Other than that, the lectures are actually very good, but the only one worth the time is the fourth one, the other three are just the first course (Linear Algebra) all over again.

By Galina F

•Jan 8, 2020

Mathematical concepts are clear, but no explanation how to apply them to python to solve machine learning ussies. But you need this for python assignments.

Scripts checking assignments work uncorrectly such a way that one can submit the same piece of working(!) code and get 0/10 and then submit the same code and get 10/10.

All in all, it's very annoying and disappointing.

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 Cy L

•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 Mojtaba B

•Apr 1, 2021

This is the worst course on in this specialization. The instructor is like a robot reading a text book. The material is not well constructed. It's just a bunch of formula after formula, with no intuition. It has a lot of readings, which is annoying in an online course. The programming assignments are challenging, but I found them useful.

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 Deleted A

•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.

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