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Volver a Mathematics for Machine Learning: PCA

Opiniones y comentarios de aprendices correspondientes a Mathematics for Machine Learning: PCA por parte de Imperial College London

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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....

Principales reseñas

WS

6 de jul. de 2021

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

16 de jul. de 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.

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226 - 250 de 706 revisiones para Mathematics for Machine Learning: PCA

por Farhan F

26 de mar. de 2022

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

por Haofei M

22 de abr. de 2020

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

por Deepak T

17 de abr. de 2020

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

por Mohammad A M

14 de nov. de 2019

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

por Alfonso J

20 de oct. de 2019

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

por MD K A

8 de ago. de 2020

Algebra, Calculus and PCA

These are all excellent, if you have mathematics knowledge

por Arijit B

5 de nov. de 2019

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

por Pascal U E

25 de may. de 2018

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

por Greg E

27 de jul. de 2019

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

por Faruk Y

22 de sep. de 2019

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

por Rodrigo S

22 de feb. de 2022

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

por Sanjay B

30 de dic. de 2020

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

por Lia L

22 de may. de 2019

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

por Pritam C

22 de sep. de 2020

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

por Nero

5 de ago. de 2022

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

por Roshan C

23 de nov. de 2019

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

por Hanif A

1 de mar. de 2021

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

por Pramod H K

7 de ago. de 2020

The highly mathematical perspective of PCA with greater conceptualization.

por Rishabh A

17 de jun. de 2019

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

por Aman M

1 de jul. de 2020

good content but assignment quality and maintenance should be rechecked

por Seelam S

25 de jul. de 2020

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

por Sanchayan D

7 de jun. de 2020

Good Introduction to understanding the principal component analysis

por Sekhar K

18 de ago. de 2021

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

por Benjamin C

28 de ene. de 2020

Excellent course regarding both theoritical and practical sides.

por Shahriyar R

14 de sep. de 2019

The hardest one but still useful, very informative neat concepts