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學生對 伦敦帝国学院 提供的 Mathematics for Machine Learning: PCA 的評價和反饋

4.0
2,088 個評分
509 條評論

課程概述

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....

熱門審閱

JS

Jul 17, 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 19, 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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451 - Mathematics for Machine Learning: PCA 的 475 個評論(共 507 個)

創建者 Scoodood C

Jul 28, 2018

Video lecture not as intuitive as previous courses.

創建者 Michael B

Nov 21, 2019

Programming assignments not well explained

創建者 youssef s a s

Jul 27, 2020

very poor explanation of things

創建者 Salah E

Aug 04, 2020

again too hard

創建者 ABHI G

Aug 22, 2018

not so good

:(

創建者 Pradeep K

Apr 30, 2020

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

Reasons:

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

創建者 Ivan F G

Jul 01, 2020

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.

創建者 Anurag G

Sep 13, 2020

I started this course with lots of enthusiasm since the previous two courses were exceptionally well structured and helpful, but I can not compare this course with those two.

The biggest problem for me was that Programming assignments are not well written and most of the time beyond the course material shared. It challenges your previous skills and may hit your self-confidence.

There are also few mistakes or/and skipped steps in the video, and they make progress little tricky.

My classmates were very helpful, and I would suggest relying more on the forums than video lectures when you need help. I would not recommend this course at all to anyone, but if you have done the first two, may complete the last one to complete the specialization.

Also, the first two courses are a few of the best certificates that I did on Machine Learning, and I have done six other mathematics for machine learning, currently enrolled for a degree course in Data Science.

All the best!

創建者 Alistair K

May 16, 2020

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.

創建者 Pavel S

Dec 13, 2019

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

創建者 Alan

Aug 04, 2020

Very disappointing compared to the other courses. Recommend a complete revision of the course materials. Quizzes often had nothing to do with the preceding video. I worked through a week two quiz using the extensive notes in the discussion forum and by searching the internet. The next lecture proceeded in the same vein: the instructor failed to cover the material in video leaving me to figure out what the material was and then figure out how to find that material on the internet or in reference books. At that point, it just was not worth the time to take the course.

創建者 周玮晨

Jun 08, 2018

This course is far far far behind my expectations.The other two course in the specializition is fantastic. There is no visualization in this course, Instructor is always doing his algebra, concepts are poorly explained. I can't understand a lot of concepts in this course because of my poor math background.But why do i take ths course if i have a solid background in math? Programming assignments is not difficult but hard to complete because of vaguely clarification.Plenty of time wasted to find what should i do, its' really frustrating.

創建者 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

創建者 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.

創建者 Horacio G D

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.

創建者 Galina F

Jan 08, 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.

創建者 Matt C

Jul 01, 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.

創建者 Cynthia M

Jun 09, 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.

創建者 Steve

Sep 05, 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.

創建者 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.

創建者 Yan Z

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.

創建者 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.

創建者 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.

創建者 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.