Chevron Left
Вернуться к Mathematics for Machine Learning: PCA

Отзывы учащихся о курсе Mathematics for Machine Learning: PCA от партнера Имперский колледж Лондона

Оценки: 2,580
Рецензии: 643

О курсе

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....

Лучшие рецензии

16 июля 2018 г.

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.

18 июня 2020 г.

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.

Фильтр по:

551–575 из 637 отзывов о курсе Mathematics for Machine Learning: PCA

автор: Maksim S

25 мар. 2020 г.

The difficulty of the course is inadequate and the pace is not balanced. Requires a lot of search for additional resources to understand materials. I cancelled.

автор: Kovendhan V

11 июля 2020 г.

After first two amazing courses in this specialisation, third course was a huge let down. One skill I learnt from this last course is patience.

автор: Martin H

8 дек. 2019 г.

Lack of examples to clarify abstract concepts. Big contrast in quality compared to the other courses in this specialization.

автор: Dipto H

7 авг. 2020 г.

Poor explanation by the instructor. Previous ones were very helpful. I didn't understand many topics well

автор: Lavanith T

21 авг. 2020 г.

Everything is okay but there is a huge drawback with the programming explanation part.

автор: Xiao L

3 июня 2019 г.

very wired assignment, a lot of error in template code. The concept is not clear.

автор: Sai M B

3 авг. 2020 г.

The lectures were not clear. I had to use other sources to understand lectures.

автор: Pawan K S

20 июня 2020 г.

This course was the hardest I encountered in this specialisation.

автор: Kirill T

26 июля 2020 г.

Way worse than the previous courses. Lacks explanations

автор: Kevin O

27 мар. 2021 г.

Really interesting topic but not nearly enough detail.

автор: Amr F M R

22 сент. 2020 г.

I think course material was not explained well at all.

автор: Timothy M

22 апр. 2021 г.

The lectures and assignments did not synergize well.

автор: Desikan S

23 сент. 2019 г.

Need to improve the content and delivery of content.

автор: Mohammed A A

19 июля 2020 г.

the course is too shallow with difficult code exame

автор: Scoodood C

28 июля 2018 г.

Video lecture not as intuitive as previous courses.

автор: Michael B

21 нояб. 2019 г.

Programming assignments not well explained

автор: youssef s

27 июля 2020 г.

very poor explanation of things

автор: Murilo F S

24 янв. 2021 г.

not good teacher :Z

автор: Salah E

4 авг. 2020 г.

again too hard

автор: ABHI G

21 авг. 2018 г.

not so good


автор: Pradeep K

30 апр. 2020 г.

Very Poor course on PCA, My recommendation. Don't watch it, Please don't waste your money on it.


1) The course on algebra and calculus was intuitive geometrically and well taught. Here the instructor bothered only doing derivations. No intuition based thinking, no analogy to real world. Just plain hard notations.

2) I don't think even the instructor would understand what was taught in the course. The excercises were completely unrelated to what was taught. Not much given examples. The examples choosen uses values like 0,1,2. Why can't you pick some odd numbers to make it bit more non confusion and clear.

3) At the end there was a review / Survey for every course. The review for this course is disabled. Clearly everyone knows how bad this is. Remove this course or make it better that is what the recommendation. There is no provision for zero stars, Had there one I would not given that also.

Really frustrated with the PCA course. Please don't waste your time and money . Get Gilbert Strang's book. That will do justice for every penny. I was able to complete the course, All thanks to Gilbert's book on Linear Algebra. Thanks

автор: Ivan F G

1 июля 2020 г.

The technical issues with Jupyter Notebooks really made me waste too many days, a lot of my time not learning but just fighting a poorly implemented exercise. And the technical issues did not help the teacher, the notebooks had a role to give us a place to learn new concepts that he mentioned in the fly, but there were no small sets of data to test the functions. I wasn't very patient with the way he will say things like "this is the formula from the previous video", and show a different formula from what he had on the previous video. Really? Why making things obscure on purpose? You can just have said, we had our previous formula and them used properties of the transpose of a product to get this other formula. Please make an effort to redo the notebooks. Even better, do some of the examples in Phyton during class for what you do in paper, and then let us take those examples and make a general function on the notebooks. Give smaller databases, something easy to plot and test, without waiting 20+minutes to have a result.

автор: Diego M E

2 апр. 2021 г.

This course by no means retains the quality of its two predecessors. The difficulty of the programming assignments simply does not match that of what you watch in the videos and have to face in the practice quizzes. You need to have at the very least an intermediate understanding of both python and numpy. It should be stated somewhere that, if you really want to try and complete the assignments with a passing grade you'd need to invest **a lot** of your time. The course does not even remotely give you the tools necessary to complete these assignments; you'll need to research on your own and consult forums, videos, manuals, etc. My advice would be to learn python to an intermediate level first, then really practice with numpy, and just after that take this course. Otherwise you'll probably get very frustrated and quit.

автор: Alistair K

16 мая 2020 г.

The instructor is extremely dry and monosyllabic and does a very poor job of explaining topics, he frequently introduces topics by jumping straight into formulas without bothering to explain the topic or the use of the subject he is supposed to be explaining.

The majority of lectures are no more that the lecturer reading our a formula parrot-fashion onto the screen, he makes no effort to make the subject informative or explain what is going on. In many cases, he doesn't even bother creating a lecture, he simply posts a link to Wikipedia.

Lectures, quizzes and assignments are littered with bugs and omissions.

A negative mark on an otherwise excellent specialisation. This lecturer has no place teaching, he made the whole subject unapproachable.

автор: Pavel S

12 дек. 2019 г.

The course has two problems:

complete lack of participation of staff in maintaining it. This leads to students giving each other incorrect advice and sharing incorrect code which passes the grader function check ( the grades are assigned automatically). The advice students give each other are frankly so wrong it is shocking.

the teacher focuses on formalised proof rather than concepts. Hence the lectures turn into lecturer applying mathematical transfomations which end in a formal argument without any intuitive understanding of the underlying subject. This course is the worst of the module with linear algebra and multivariate calculus being much better