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学生对 Imperial College London 提供的 Mathematics for Machine Learning: Linear Algebra 的评价和反馈

4.7
12,504 个评分

课程概述

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....

热门审阅

HE

Aug 8, 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

CS

Mar 31, 2018

Amazing course, great instructors. The amount of working linear algebra knowledge you get from this single course is substantial. It has already helped solidify my learning in other ML and AI courses.

筛选依据:

1826 - Mathematics for Machine Learning: Linear Algebra 的 1850 个评论(共 2,468 个)

创建者 moksha m

Jul 16, 2020

good

创建者 AKSHATHA Y E

Jul 16, 2020

Good

创建者 Bhoomika H

Jul 15, 2020

good

创建者 BALAJI.V

Jul 13, 2020

Good

创建者 RAMÍREZ S C A

Jun 29, 2020

Nice

创建者 Nalongsone D

Jun 16, 2020

good

创建者 Vinish R

May 12, 2020

nice

创建者 eli z

Apr 12, 2020

epic

创建者 Akhil V

Jul 31, 2019

good

创建者 Salem A A

Jul 1, 2019

Good

创建者 宋健

Mar 12, 2019

nice

创建者 Yiqing W

Dec 27, 2018

good

创建者 Johnny B

Nov 18, 2022

ook

创建者 MD K A

Jul 14, 2020

Osm

创建者 임모세

Jun 3, 2024

bb

创建者 Daniel R

Aug 12, 2018

A+

创建者 Deepak K A

Jun 19, 2018

:)

创建者 Joseph S

Sep 27, 2021

创建者 Rayanne

Oct 21, 2019

j

创建者 Tushar S

Mar 27, 2019

.

创建者 John F

Apr 23, 2020

It's a good overview. I think that to get a lot out of this course it would help to have at least encountered basic matrices, vectors etc before. It's not that these concepts aren't introduced it's just that I can imagine if you have never encountered these things before you might get overwhelmed a bit quickly. It would also help if you have some rudimentary knowledge of programming i.e. know basic syntax, what a for loop or a while loop is and other basics. I know a bit of programming and i'm pretty ok at math so the course was manageable for me. Especially good was showing how all of the concepts learnt can be applied to understanding the Google Page Rank algorithm.

The best part of this course is the conceptual overview it gives and the instructors constantly reiterate how this type of understanding is more important than just being able to chug through a whole lot of algebra. Computational skills aren't really that important because apart from very basic examples, a computer is pretty much necessary to do the calculations anyway and as we all know, just because you know how to plug stuff into a formula doesn't mean you have the faintest idea what you are actually doing!

I think a very bright person could probably fully understand this course coming at it from scratch but I know that I would have struggled if i'd never glanced at the math or done some basic programming before.

创建者 Aditya K

Jan 5, 2024

While this course helped me broaden my knowledge and understanding of Linear Algebra, I still won't give it a 5 star rating. And that's because I feel that the course doesn't match its content for its target audience. The graded assignments and the practice quizzes are way too hard for the content taught. More time needs to be given to each topic to justify the difficulty of the quizzes. Before taking up this course, I had been doing linear algebra for the past 3 years. And even I had to face some difficulties in clearing the graded quizzes. I can't imagine the plight of an absolute beginner. Nonetheless, for me personally, this course was a good refresher and strengthened my fundamental knowledge about linear algebra. Dr David was phenomenal in teaching the core concepts.

创建者 Vern

Apr 10, 2018

I would give this course 5 stars for the fact that in five weeks, the course is able to go through perhaps a semester or two or three of Linear Algebra (LA), and how LA fits into data science. I gave it four stars because I believe the program should include lots of links to reference and learning aid resources. Because I had done a couple other courses on LA relatively recently, some these arcane LA concepts were grasped with some, but not too much, effort.

If you are even just a little familiar with LA, this course will give you a good foundation for the LA relative to data science. So, if this is you, and you want to get into Machine Learning (ML) to understand how ML works internally, then jump right in.

Thanks to all who contributed to make this a great ride.

创建者 Vy H

Sep 9, 2021

Despite having learnt about vectors and matrices in the past, I still find this course challenging at time due to incompleteness of lecture contents. But researching and thinking through these issues did help me better understand the course material. The instructors have a different view on teaching maths in the age of computers. Instead of focusing on solving equations, the main focus of the course is on building an intuitive understanding of the mathematical concepts. And they deliver on this promise. I also appreciate the effort to select only materials relevant to ML. This saves students lots of time and effort.

创建者 John G

Sep 30, 2018

Overall, the course is good and well worth your time if you goal is to brush on Linear Algebra. It is pretty important that you have been exposed to linear algebra before though, as some topics are covered pretty quickly. My only complaint is that there was a lot of unnecessary obfuscation. The lectures constantly alluded to things without actually naming them (e.g., gradient descent in one of the earlier lectures). I found the "Essence of Linear Algebra" video series on YouTube to be invaluable to actually making sense of some of the lectures in this course, so if you do take this course I suggest doing the same!