Вернуться к Mathematics for Machine Learning: PCA

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

4.0
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Оценки: 2,544
Рецензии: 629

## 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

JS
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.

NS
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.

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## 576–600 из 624 отзывов о курсе Mathematics for Machine Learning: PCA

автор: Matt C

1 июля 2018 г.

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.

автор: Cy L

9 июня 2018 г.

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.

автор: Mojtaba B

1 апр. 2021 г.

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.

автор: Kannan S

11 апр. 2018 г.

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.

автор: Gassysoil

13 окт. 2019 г.

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.

автор: Rob E

11 авг. 2020 г.

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.

автор: Kristina S

24 авг. 2018 г.

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.

автор: Oliver K

21 февр. 2020 г.

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.

автор: kumar s

11 авг. 2020 г.

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.

автор: Deleted A

31 янв. 2020 г.

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.

автор: Ashlee H

26 нояб. 2019 г.

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.

автор: Ed W

25 нояб. 2019 г.

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.

автор: Christiano d S

10 авг. 2020 г.

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.

автор: Kimberely C

27 дек. 2019 г.

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.

автор: Gurrapu N

9 апр. 2020 г.

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.

автор: Marcin

19 авг. 2018 г.

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.

автор: Danielius K

24 сент. 2019 г.

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.

автор: Saransh G

28 апр. 2020 г.

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

автор: Tai J Y

16 нояб. 2019 г.

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.

автор: Vibhutesh K S

17 мая 2019 г.

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

автор: Alejandro T R

2 авг. 2020 г.

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

автор: Ananya G

28 дек. 2019 г.

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

автор: Yap C Y

7 мар. 2021 г.

Explanations need to be clearer. Efforts are needed in explaining the details of every components in this course.

автор: Michael K

30 нояб. 2020 г.

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