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

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10,791 Bewertungen
2,149 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.

HE

8. Aug. 2021

the instrutors were too good and their explination for the concepts was to the point and it made me realize things in linear algebra I didn't know before although I studied it in school of engineering

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1726 - 1750 von 2,161 Bewertungen für Mathematics for Machine Learning: Linear Algebra

von Deval P

10. Juli 2020

even though my code was right in the last assignment the grader kept getting timed out. it took 3 days to work and in the end the code was same. the course on the other hand was quite good and easy.

von Jorge V

11. Nov. 2018

Great content and direction. Only negative is the sometimes frustrating experience with the Jupyter Notebooks: debugging what has gone wrong is very difficult, due to a lack of good error messages.

von Marco K

30. März 2020

Be careful as a beginner in coding. It might be frustrating from time to time. I have spent the majority of my timing on the coding . At the end worthwhile, but did not feel that way at that time

von Milan S

8. Mai 2018

Good, but sometimes it is neccessary to look for supporting materials. I took this course in combination with MIT course in LA and this offered another, more practice oriented, view on the topic.

von Tanmoy D

7. Juni 2018

The course is a great resource to brush up on the fundamentals of linear algebra and learn about the meaning behind the math.It prepares people for any further courses which use linear algebra.

von Keshav B

13. Juni 2020

This course was very insightful. The instruction was well done with expressing the intuition, but the process was left vague on a few concepts and required me to look up worked out examples.

von Lalpekhlua L

17. Juli 2021

I think it is a great course. It is definitely not for beginners and I feel the lectures are somewhat rushed on some videos. It is best to view this course as a supplement and not as a main

von Sharon I

27. März 2022

good videos and good instructors; programming assigments could be a little bit clearer in the instructions. Overall good for understanding the maths behind Machine Learning. Thank you!

von shashank s

17. Feb. 2020

The course was good but it could have been better if the exercises had more difficult questions or probably a section with more difficult questions using the concepts that were taught.

von ASIFIWE E

2. März 2021

This is excellent course provided as fundamental skills required in Machine learning journey. I was excited to be learn from best lecturers ever and, thanks to Imperial College.

von Gurudu S R

18. Aug. 2019

1.Need more clarity on calculating Eigen vectors using back substitution of Eigen values.

2. Power Iteration method for the Page Rank Algorithm should be more specific and clear.

von Phuong N

24. Sep. 2018

The course can help me more clearly when approach some algorithms in the optimize function of Machine learning. Thanks coursera and Imperial London College about this course.

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von Tom F

28. Dez. 2021

A really well structured course, a few minor problems with the coding assignment formatting but otherwise all the topics were covered in depth with plenty of application tests.

von Sri C D

16. Juli 2020

The instructors and the way of their explanation are a huge benefit of this course. The intuition they provided each step in Linear and Vector Algebra are really appreciable.

von Elliott P

30. Apr. 2019

It's a very good course given that it's so short. It was exactly what I was expecting. I thought it could have had more examples of solving problems with specific techniques.

von Sastry

11. Apr. 2018

Very interesting presentation of matrices and vectors. The questions in quizzes could be improved by making them clear. May be you could add another course on eigen analysis.

von NAVEEN R

2. Aug. 2020

Topics are explained neatly but lacked in depth explanation in few topics and i suggest to include more application oriented examples to every topics covered in the course.

von Amer M

28. Juni 2020

Good Course, It shows Linear Algebra from different perspective. You should not be good in math because the math is not advanced here, but you should be excellent in Python.

von Alek C

7. Dez. 2020

This course is can be challenging but the material is good and i trust this over a university program since this course is applied concepts and works with lite programming.

von rezvaneh z

19. Apr. 2020

It really was useful, but need a little bit more concentrated discussion forums. cause many questions were still unanswered there.

but thank you all, it really helped me :)

von JAY C

30. Juni 2019

I think the concepts are explained clearly, with ample examples to real life. Much easier to understand this time around. The coding labs could use more pointers though.

von Victor D

14. Juli 2020

it is quite intuitive, the programing tools are easy to use. I think its perfect for those people who have some math background but don't want to go deeper into theory

von Jaumir V D S J

17. März 2019

The course by no means replace a full semester course on linear algebra, but it´s useful for those who had already had a course on L.A. years ago and want a refresher.

von David G R A

4. März 2021

All the lectures were great, and pretty straightforward, but, some programming assestments were too dificult and not so useful in order to help to grasp the concepts.