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Learner Reviews & Feedback for Mathematics for Machine Learning: Linear Algebra by Imperial College London

4.7
stars
10,706 ratings
2,130 reviews

About the Course

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 reviews

NS

Dec 22, 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

Sep 9, 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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1676 - 1700 of 2,141 Reviews for Mathematics for Machine Learning: Linear Algebra

By RITIK D E

May 1, 2020

Course was very interesting but found some difficulties in the assignment section as it took almost hour to understand it. But, the course was very nice and also it help me to recollect all the mathematics part of Linear Algebra that I've studied earlier.

By Aarón M C M

Jun 5, 2019

I am a computer scientist and this course served me to refresh all that concepts and exercises that I studied at the university, I only would ask to improve of the notebook's availabilty because sometimes I got disconnected and had to start all over again.

By Akiva K S

May 30, 2020

Multiplying 2x2 matrices by hand drives me crazy! Why instructors waste precious online time on that crap? Two, three matrix multiplications by hand during the lecture is perfectly OK with me, but why to do it over and over? The same with the exercises.

By Xiaocong Y

Feb 15, 2021

Good for beginner, but relatively easy if you have backgrounds in Linear Algebra. The course focus on making you adopt intuitions of how Linear Algebra is actually working geometrically which may be interesting if you only knows how the algebra works.

By Joshua P

Jul 9, 2020

As someone with a bit of a background in linear algebra, this course is perfect in being a refresher to the said course. But unfortunately, especially for those who are completely new to the subject, the hurried explanations will leave some confused.

By Jehan T

Aug 9, 2020

Great course, especially the first 4 weeks with David Dye. Unfortunately the lecturer in the 5th week is much harder to follow, and I needed to reference some additional youtube videos outside the course to get an intuitive grasp of the concepts.

By David B C

Sep 8, 2018

Great lectures and wonderful scrutiny of matrices and vectors. Exploration of machine learning using Python, but the interface and project upload are somewhat kludgy. Stick with it and you can get the fundamentals even if the coding doesn't work.

By Priadi T W

Sep 7, 2019

The course was great for me. It opens up new perspective to some vector and matrix application. However, I must admit that you must have strong background with math before taking this course, as I was little bit struggling with matrix part.

By Marcin

Jun 4, 2018

It's by far the toughest course that I've done on Coursera. And at the same time the most rewarding upon completion. The course content is very applicable in the real world and it's definitely something that any ML specialist should know.

By Srinivas A

Jul 7, 2020

Great content, well explained, it's an overview of Linear Algebra relevant to Machine Learning, not a full blown course. Some of the assignments need clarity, especially the Python assignments. There is no faculty/staff to ask questions.

By Mikko V

Aug 1, 2018

The lectures are excellent, but the scarcity of traditional math assignments prevented intuitive and reinforced learning. Thus the course should be considered a brief glance at linear algebra, rather than a proper course on the subject.

By Yadla V C

Oct 19, 2020

This Course takes you to the deep dive of Linear Algebra. But the lectures are not sufficient to solve assignments. We can make use of the resources given by Instructors for clear understanding of core concepts of Vectors and Matrices

By Godugu A H

Nov 30, 2021

T​he course overall is very good. The only drawback I felt was the lack of numerical examples to intepret complex linear algebra formulae. I would love to see videos carrying more worked examples of the formulae learnt in the course.

By Gady

Mar 26, 2020

The pedagogy could use some reviewing, but the concepts and especially the reviews are generally laid out logically, and relatively easy to go through. Still recommend looking up things on the side through YouTube when you're stuck.

By Rohit S

Mar 3, 2020

There were many concepts which were totally new to me and many were known to me but I couldn't relate them with the machine learning problems now an I am able to do all those problems easily so thanks a lot Coursera and ICL team.

By Akshay V

Jul 14, 2020

It is a good course on Linear Algebra. The teaching was excellent, all the assignments were challenging with some easy ones in the middle to boost your learning process, altogether I am happy to cover it with good understanding.

By Mit S

Feb 24, 2020

This course has great content and great way of teaching by instructors however the instructions in the programming exercises is not very clear. I hope the instructors take note of that. Overall, a fantastic Course content wise!

By Sekhar G

Aug 20, 2020

Being at an advance level of study, this course seems to easy to me but what I recommend is that any undergraduate or postgraduate student will definitely gain many interesting facts about linear algebra from this course.

By Carlos M V R

Jul 25, 2020

It could be good to have more explanation about eigenvalues and eigenvectors because it is an important topic for data science. In general it is a very good course, you explained many topics in a simple and funny way.

By Arnab S

Jun 21, 2020

I enjoyed learning in this course. There are a lot of different aspects that are covered here which is very interesting but I course is not for absolute beginners. It will be better if someone has a bit of background.

By Bassiehetkoekje

Feb 27, 2019

Nicely structured courses with enthusiastic teachers. Interactive enough to keep you thinking (which is key).

Some errors here and there and short moments of not enough explanation. But all in all an enjoyable course.

By Naser A A

Jul 11, 2020

Great course to understand how linear algebra is related to machine learning. Focused on the concepts, and the concepts work rather than calculations. Would be easier if there was prior knowlodge of python and numpy.

By Cici

Jul 12, 2019

This is a great course. The only thing is sometimes the calculations are hard to follow. I wonder if it is possible to let viewers click through a calculation process at their own pace. But the instructors are great!

By Mrunal U

Jul 20, 2020

excellent course to understand the linear algebra as a tool for problem solving in machine learrning though it not help directly but give you the strong understanding the fundamentals which will help in the future

By Snigdha A

Oct 13, 2020

Excellent course. I just wish the assignments were a little harder. The last assignment was the perfect toughness level. Made me connect concepts, look up stuff and actually get out of my comfort zone to learn.