Chevron Left
Zurück zu Mathematics for Machine Learning: PCA

Bewertung und Feedback des Lernenden für Mathematics for Machine Learning: PCA von Imperial College London

4.0
Sterne
2,866 Bewertungen

Über den Kurs

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....

Top-Bewertungen

WS

6. Juli 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. Juli 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.

Filtern nach:

1 - 25 von 712 Bewertungen für Mathematics for Machine Learning: PCA

von Hashaam S

30. Dez. 2018

von Maximilian W

29. Apr. 2019

von Eric P

26. Apr. 2019

von Vyacheslav T

24. März 2019

von Christos M

27. Apr. 2019

von Avirup G

18. Feb. 2019

von Alexandra S

26. Sep. 2018

von Bryan S

19. Feb. 2019

von Sreekar P

23. Okt. 2018

von Harshit D

30. Juli 2018

von Brock I

21. Nov. 2018

von Guillermo A

15. Juni 2020

von Rahul M

29. Juni 2019

von Roy A

23. Sep. 2020

von Nimesh S

19. Juni 2020

von João S

2. Mai 2019

von Martin B

22. Okt. 2018

von Jong H S

17. Juli 2018

von Oliverio J S J

29. Mai 2020

von Christian R

24. Juli 2018

von JICHEN W

27. Okt. 2018

von Jayant V

1. Mai 2018

von José D

31. Okt. 2018

von Thomas B

4. Juni 2022

von A h b

21. Okt. 2019