Mathematics for Machine Learning: PCA(으)로 돌아가기

4.0
별점
2,835개의 평가
708개의 리뷰

## 강좌 소개

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....

## 최상위 리뷰

WS

2021년 7월 6일

Now i feel confident about pursuing machine learning courses in the future as I have learned most of the mathematics which will be helpful in building the base for machine learning, data science.

JS

2018년 7월 16일

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.

필터링 기준:

## Mathematics for Machine Learning: PCA의 706개 리뷰 중 676~700

교육 기관: Saransh G

2020년 4월 28일

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

교육 기관: Tai J Y

2019년 11월 16일

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.

교육 기관: Vibhutesh K S

2019년 5월 17일

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

교육 기관: Alejandro T R

2020년 8월 2일

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

교육 기관: Ananya G

2019년 12월 28일

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

교육 기관: Sherif B

2021년 5월 3일

Very bad experience, skips steps, does not reflect on intuitions like other courses in the specializations, monotonous.

교육 기관: Yap C Y

2021년 3월 7일

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

교육 기관: Michael K

2020년 11월 30일

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

교육 기관: Nithin K

2018년 6월 5일

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

교육 기관: Kamoliddin N

2020년 1월 28일

교육 기관: Sairam K

2021년 1월 9일

The course videos provide insufficient and/or misleading context for the assignments.

교육 기관: Daniel C

2021년 8월 20일

​the lecture videos do not seem to provide enough guidance for the assignments

교육 기관: TUSHAR K

2020년 7월 19일

Previous Two Courses were better in terms of both assignments and teaching.

교육 기관: Siddharth S

2020년 6월 4일

Very Poor when compared to previous two courses of this specialization.

교육 기관: Saeif A

2020년 1월 1일

This course was a disaster for me. The first two were great though.

교육 기관: Jared E

2018년 8월 25일

Impossible to do without apparently an indepth knowledge of python.

교육 기관: Soumitri C

2020년 12월 15일

okayish teaching but grading system is absolute rubbish in Week4

2020년 7월 4일

Very poor teaching and overall it's the worst course I've taken

2020년 8월 27일

Very bad explanation. The assignments need more instructions.

교육 기관: Aurel N

2020년 7월 5일

k-NN assignment is full of errors and no proper explanations.

교육 기관: Wensheng Z

2019년 11월 24일

Jumpy instruction with little illustrations

2019년 10월 31일

Worst course I've ever taken, online or IRL

교육 기관: Zecheng W

2019년 10월 19일

Poorly organized and extremely confusing

교육 기관: Mingzhe D

2019년 12월 11일

Assignment 1 cannot be passed!

교육 기관: ML-07 C k

2021년 3월 2일

confuse , difficuld and weird