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Mathematics for Machine Learning: PCA(으)로 돌아가기

임페리얼 칼리지 런던의 Mathematics for Machine Learning: PCA 학습자 리뷰 및 피드백

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


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.


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 226~250

교육 기관: Farhan F

2022년 3월 26일

T​his is very very very very very challengging, but i can do it because i try try and try

교육 기관: Haofei M

2020년 4월 22일

extremely informative and really help me understand the basic math in Machine learning

교육 기관: Deepak T

2020년 4월 17일

Course was challenging, so does the math. It was a very excellent learning experience!

교육 기관: Mohammad A M

2019년 11월 14일

This course is also so helpful, and the lecturer is so predominant on what he taught.

교육 기관: Alfonso J

2019년 10월 20일

Truly hardcore course if your are a noob in reduced order modelling. Very challenging

교육 기관: MD K A

2020년 8월 8일

Algebra, Calculus and PCA

These are all excellent, if you have mathematics knowledge

교육 기관: Arijit B

2019년 11월 5일

Excellent course and extremely difficult one to grasp at one go. Regards Arijit Bose

교육 기관: Pascal U E

2018년 5월 25일

Very hard to follow, but you need to do it to understand machine learning very well.

교육 기관: Greg E

2019년 7월 27일

I have thoroughly enjoyed every course of this specialization. Thank you very much.

교육 기관: Faruk Y

2019년 9월 22일

Lectures and programming assignments were selected nicely to teach the math of PCA

교육 기관: Rodrigo S

2022년 2월 22일

Amazing course, really challenging tho, however, material lerned is very useful.

교육 기관: Sanjay B

2020년 12월 30일

Excellent program, helped get to understand features of Python programming fast

교육 기관: Lia L

2019년 5월 22일

This was really difficoult, but I'm so proud for the completion of the course.

교육 기관: Pritam C

2020년 9월 22일

It was an intense Math Class with a piece of new knowledge about PCA...Thanks

교육 기관: Nero

2022년 8월 5일

The instructor is doing a great job in explaining the mathematics behind PCA

교육 기관: Roshan C

2019년 11월 23일

the course was very much intuitive and helpful to grasp the knowledge of PCA

교육 기관: Hanif A

2021년 3월 1일

I think there must be correction for the pca lab, the testing code is error

교육 기관: Pramod H K

2020년 8월 7일

The highly mathematical perspective of PCA with greater conceptualization.

교육 기관: Rishabh A

2019년 6월 17일

We need more elaborate explanation at few tricky places during the course.

교육 기관: Aman M

2020년 7월 1일

good content but assignment quality and maintenance should be rechecked

교육 기관: Seelam S

2020년 7월 25일

Good Course to get knowledge of Maths required for Machine Learning! ☺

교육 기관: Sanchayan D

2020년 6월 7일

Good Introduction to understanding the principal component analysis

교육 기관: Sekhar K

2021년 8월 18일

Excellent course! Really enjoyed it. All professors were great!!

교육 기관: Benjamin C

2020년 1월 28일

Excellent course regarding both theoritical and practical sides.

교육 기관: Shahriyar R

2019년 9월 14일

The hardest one but still useful, very informative neat concepts