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

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10,706 Bewertungen
2,130 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.

EC

9. Sep. 2019

Excellent review of Linear Algebra even for those who have taken it at school. Handwriting of the first instructor wasn't always legible, but wasn't too bad. Second instructor's handwriting is better.

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1876 - 1900 von 2,141 Bewertungen für Mathematics for Machine Learning: Linear Algebra

von Abhirup B

29. Juli 2020

goood course well designed qizes and aasignments time saving yet fruitful

von Julian A

12. Juni 2020

Fantastic course that provides a great introduction into linear algebra.

von Ivan

4. Juni 2018

The course content is good, but the programming assignment is too easy.

von Ritik j

1. Juni 2020

some topics are explained in a typical way and a bit problem was occur

von I M N P M

24. Feb. 2021

The eigen value and eigen vector courses are a bit hard to understand

von Kevin O

25. Feb. 2021

A good refresher with some really useful insights about eigenthings.

von KIRANKUMAR M

21. Juli 2020

Its is the best course to know about matrices and their applications

von Sharad K L

9. März 2020

Exams were hard and most of the exams were source of the knowledge.

von JOSÉ M B D

25. Jan. 2020

excelente curso, me gustaría que se complementara con programación.

von Jihun Y

3. Jan. 2022

teaching essential, doesn't cover many topics, but well curated!

von Sai V P

14. Aug. 2020

Decent course. Wish things were explained in a more detailed way

von Ng Y Y

21. Juni 2019

Good overview and introduction to key concepts of linear algebra

von Mohammed K A

12. Feb. 2022

n​eed some use of visualisation in some topic like change basis

von fatima s

18. Juni 2020

Wish it was a bit more spontaneous but overall great content!!

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