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

4.7
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11,348 Bewertungen

Über den Kurs

In this course on Linear Algebra we look at what linear algebra is and how it relates to vectors and matrices. Then we look through what vectors and matrices are and how to work with them, including the knotty problem of eigenvalues and eigenvectors, and how to use these to solve problems. Finally we look at how to use these to do fun things with datasets - like how to rotate images of faces and how to extract eigenvectors to look at how the Pagerank algorithm works. Since we're aiming at data-driven applications, we'll be implementing some of these ideas in code, not just on pencil and paper. Towards the end of the course, you'll write code blocks and encounter Jupyter notebooks in Python, but don't worry, these will be quite short, focussed on the concepts, and will guide you through if you’ve not coded before. At the end of this course you will have an intuitive understanding of vectors and matrices that will help you bridge the gap into linear algebra problems, and how to apply these concepts to machine learning....

Top-Bewertungen

NS

22. Dez. 2018

Professors teaches in so much friendly manner. This is beginner level course. Don't expect you will dive deep inside the Linear Algebra. But the foundation will become solid if you attend this course.

PL

25. Aug. 2018

Great way to learn about applied Linear Algebra. Should be fairly easy if you have any background with linear algebra, but looks at concepts through the scope of geometric application, which is fresh.

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1976 - 2000 von 2,243 Bewertungen für Mathematics for Machine Learning: Linear Algebra

von Gautam K

7. März 2019

Highly recommended course for beginners in Machine Learning.

von Mark R

3. Jan. 2019

Good grounding in the fundamental mathematics needed for ML

von Alagu P P G

18. Juni 2020

good start up for algebra enthusiasist.

a strong foundation

von Deleted A

23. Apr. 2020

I felt that lectures aren't enough to solve the exercises.

von celwang

23. März 2020

good course ! but some of the formula should be more clear

von 谢迟

25. Juni 2018

The core idea of eigenvalue and eigenvector is very good.

von Andini A M

12. März 2021

I thought it was lacking in practice before the LAB test

von Pakpoom S

6. Aug. 2021

Good course but should dig more deeper in math concepts

von stark

6. Feb. 2021

Inspired me how to look at matrix, but not deep enough

von Alisa G

25. Apr. 2020

great teachers, very practical quizzes and examples!

von Monhanmod K

10. Okt. 2018

not bad, I feel the information is not enough for ML

von Rahul S

21. Juni 2020

like a building blocks for one step forward into AI

von Aniruddhan P N

29. Mai 2020

Excellent Introduction to the concepts, Thank you!

von adam m

12. Feb. 2019

reasonably well constructed and presented material

von Abhishek J

19. Apr. 2020

Good Course, Best Videos, Excellent Understanding

von Manish C

16. Apr. 2020

well made course for machine learning foundation

von Tasfiq R

29. Juni 2020

Great course.Animation can be addes for pagerank

von Kasidit ( R

21. März 2019

Great way to build foundation in Linear Algebra

von Jay S S

27. Juli 2020

Fast paced interesting course. Lots to learn!

von Uri M

29. Sep. 2020

Pretty nice hands on linear algebra course

von 何霄

23. Feb. 2020

clearly explain all the key concepts in la

von Ratnakar M

1. Juni 2018

Very engaging course and right on spot!!!

von Andres O

25. Mai 2018

Very good linear algebra intro/refresher

von Paul M D C B

2. Nov. 2020

Too technical but relevant nonetheless

von Manikanta G

22. Aug. 2020

it's worth taking to revise the topics