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Mathematics for Machine Learning: Linear Algebra(으)로 돌아가기

임페리얼 칼리지 런던의 Mathematics for Machine Learning: Linear Algebra 학습자 리뷰 및 피드백

4,603개의 평가
833개의 리뷰

강좌 소개

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....

최상위 리뷰


Aug 26, 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.


Sep 10, 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.

필터링 기준:

Mathematics for Machine Learning: Linear Algebra의 830개 리뷰 중 26~50

교육 기관: Kris S

May 28, 2019

Very good course: well paced, well structured, just the right scope.

교육 기관: khaled W S

Mar 25, 2019

totally enjoyed it. requires a bit of side research as any online course would. some of the quizzes were not directly related to the video that preceded them as one would expect. However, a fun course and covers a lot of important basics for it's relatively short duration.


May 17, 2019

This course reviews the essential concept of linear algebra in the context of machine learning. However, it would be much better if it provided more optional exercise and reading materials.

교육 기관: Ralph T

May 04, 2019

decent course. It gives a good enough background to understand the mathematics necessities of many areas of data science. could be more thorough and dive deeper into some of the content.

교육 기관: Mark J T

Aug 02, 2019

Good course because it shows how to understand geometrically, things that I had hitherto only understood computationally.

교육 기관: Philip A

May 16, 2019

Excellent Instruction

교육 기관: Maytat L

Nov 20, 2019

Challenging course. Much more difficult that I expected. It took me 7-9 hours a week. The overall course material itself was good building-blocks to further understand application of machine learning. However, explanation in some topics should have more detailed explanation and examples to further understand the concept. There were many times, I need to re-watch each video over and over again, paused it, and figured things out on my own. The programming assignments were the most challenging task. I just began to learn Python and found it very difficult because there were so many codes I haven't learnt before. I think for those who has not learnt Python at all may find really really difficult to pass the assignments.

교육 기관: Peter B H

Nov 27, 2019

The content was good, but a couple of times what was said didn't gel with what was being drawn/written/done. Since I'm learning, this took me longer to double check when I misunderstood something whether it was the concept or a mistake in the delivery.

교육 기관: Pedro C O R

Aug 02, 2019

The topics could be improved in the way they are presented. I always had to search for additional material.

However, the course is okay, it could be better, the forum is not that active, and some assignments are good.

교육 기관: kai k

May 05, 2019

many of the activities are excellent, but videos hard to follow along to at times - play them at 0.75 speed if you can. Also, the faculty is not super responsive it seems on discussion boards creating some confusion

교육 기관: Girisha D D S

Aug 27, 2018

Although the course content is good, I feel it could have been done better. I enjoyed the multivariate calculus course compared to this course.

교육 기관: Maximilian P

Dec 12, 2018

Some exercises are completely incoherent to the preceding videos, which makes it very difficult to solve them. very frustrating

교육 기관: Mesum R H

Aug 26, 2018

The course tries to cover every edge of Linear Algebra but fails to integrate each step with what relationship it has with Machine Learning. Core Formulas and Mathematical derivations are shoved down from throat without any respect for learners from non-engineering or computer science background. Other than week 1,2 rest was completely case study or example less UN-intuitive lectures of matrix formations and transformations. Needs a severe revamp with better examples and broader picture.

교육 기관: Anonymous

May 09, 2018

The content and the speed are not satisfactory.

The speed totally hampers the content, lots of things aren't explained especially after Sam took over in the last module.

Other than the first 2-3 intuition videos and the programming assignment nothing was good in the 5th module/week.

It was very very difficult to follow the page rank video. I still don't understand it. For eigen basis I had to refer to other material outside this course.

교육 기관: Jorge N G

May 02, 2018

Mainly explains how to operate with matrices and vectors. Not how to use those in machine learning. If you expect to have a clear view of the usefulness of eigenvectors and eigenvalues in machine learning, this is not your course.

교육 기관: Arno D

Dec 19, 2018

Some concepts were not clearly explained and there were a lot of issues with assignment grading working properly.

교육 기관: PRAKHAR K

Mar 11, 2018

Not good, concepts not explained clearly.

교육 기관: Richard C

Oct 16, 2018

Does not explain mathematics in videos

교육 기관: Dmitry R

Jan 13, 2019

Authors try to teach babies. Might be good, it is hard to judge for me as I know linear algebra. Definitely boring to me. For example 3Blue1Brown (which they reference btw) is ingenious in my opinion, so it might be not me who is the problem.

But the quizzes just don't make sense! The ones where solving problems involved might have 2 numerically right answers but only one of two is treated as the right. And there are just idiotic or not covered in lectures answers for quizzes without problems.

교육 기관: Patrick B J

Jul 25, 2018

Hands down the worst course I've ever taken in my life! Poorly put together and extremely short videos that don't provide an adequate amount of knowledge especially in relationship to the given quizzes. I truly hope this course is removed.

교육 기관: sitsawek s

Sep 14, 2018

Quite difficult for learner who didn't know about linear algebra.It jump and few example and skip a lot of part for understand.But good for recall.

교육 기관: Edik A

Aug 01, 2019

This course is excellent however it is not for the mathematically immature unless they are willing to put quite a bit of additional work in. Arguably it can be classed as "Beginners" but still, I can imagine many will feel lost very quickly. At one stage David Dye offhandedly mentions soh-cah-toa... and that really sums up a lot of what is required in terms of mathematical maturity - high school maths at a reasonable level.

Those that undertake the course should be assisted by referring to additional materials when they feel things are a bit of a struggle, I did, and this greatly helped, although my Maths was around UK high school level (in Algebra and Trig).

Overall first class and easily manageable with a little work!

교육 기관: Marco G

Nov 10, 2019

Great class to build an intuitive understanding of the concepts. The topics covered are not as many as in a serious course in linear algebra, but the ones covered really help you get to a genuine understanding. The assignment basically consist in rewriting in python what you see in the slides. If you are familiar even at a very basic level with Python, it will take you less than 5 minutes to complete the assignments, they are not challenging at all in that sense. But they do help visualize what is taught in the vides, which I guess is the purpose. To conclude, I would suggest paying for this course only if taking the full specialization, otherwise simply watch the videos for free!

교육 기관: Timo K

Mar 28, 2018


Amazing explanations of the covered topics, extremely engaging teaching staff

Focusses on the right things

Good and enough practice problems

Great (albeit easy) programming problems


Calculation of Eigenvectors could have been covered better in my opinion

A final handout for all the covered topics would be really nice

Overall a tremendous course if you want to brush up on linear algebra. To me LA was taught mostly doing rote calculations without motivating the concepts or explaining them geometrically. I had more than a handful of "oh, so that's how this actually works" moments. I feel like my intuitive understanding of linear algebra concepts has made a big improvement.

교육 기관: John F

Jun 01, 2019

This course is the first of 3 Machine Learning Math courses in this specialization which I am taking because I desperately need it as a refresh and as preparation to take Andrew Ng Machine Learning Course in the very near future. So I am 1/3 of the way there to being ready to take Andrew Ng famous and highly regarded Machine Learning Course. I began taking it but after 3 weeks, It became apparent that I needed this so that I can actually grasp and understand the material. I am so looking forward to starting it over again here shortly after I finish these next 2 fundamental prerequisites as I regard them

Kind regards,

JeanPierre (John Fisher)