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Back to Mathematics for Machine Learning: Linear Algebra

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

4.7
stars
10,259 ratings
2,060 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

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.

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1926 - 1950 of 2,067 Reviews for Mathematics for Machine Learning: Linear Algebra

By Steve

Jul 4, 2020

The course starts well and in general the first instructor does a good job trying to help the student develop an intuition of the concepts. However, weeks 4 and 5 are extremely weak. Very important concepts like eigenvalues and eigenvectors are poorly explained. The final quiz on these concepts asks questions that were never discussed or explained in the videos. I found I needed to go elsewhere on the Internet (like 3Brown1Blue) just to help me get through some of the quizes.

By Alois H

Feb 18, 2021

Teaching quality is good overall, except for a few jumps towards the end, where it's hard to follow. Quizzes and assignments well designed.

Unfortunately, and contrary to other courses I've taken, the forum seems completely un-monitored (as of May 2019), so don't expect much help from there.

Overall it's a good start of the specialization. Sadly, the teaching quality of the other two courses (multivariate calculus and PCA) is way below the standards of this one.

By k i

Jun 28, 2021

Without about intermediate knowledge on vectors, you would be having a tad difficult time doing this course. I have already studied Linear Algebra in my University, attaining an A grade and found the explanation for some of the parts a bit confusing. It is not bad by any means, but just that I believe a more structured/concise explanation for some of the terms might be more accessible for beginners or students who have never learned about Lin Alg before.

By Adam T

Nov 7, 2021

The course was informative on most of the Linear Algebra you need for machine learning. The programming assignments and quizzes are mostly relevant to what you learn beforehand. However, some of the videos feel rushed and I found it difficult to take notes in time without having to replay the videos. There is also a lack of written content after each video describing the content covered, which would have been a godsend for me with my method of learning.

By Matthew H

Mar 16, 2021

Definitely enjoyed some parts of the course but in general, the explanations are brief, requires spending significant time outside of videos on Youtube, discussion boards etc as they skip or miss key points for a beginner to grasp Linear Algebra concepts. Happy that I completed the course, but a lot of improvements should be made by including course notes that supplement common queries/misunderstandings students have in relation to the course materials.

By Xinhui Y

Sep 8, 2020

This course is not very hard for students with some maths foundations like me, but the programming assignment is too hard, even though I knew some basic Python knowledge. Two lecturers sometimes could not explain one concept clearly with some typical examples. I could only learn by doing assignments or use formulas to calculate without real understanding. This course is only for some basic concepts but not solid learning.

By Chika

Jun 13, 2019

The videos were well structured, but the quiz sometimes were far more difficult than the practice questions in video. I had posted on forum but no comment nor reply. Quiz answers were not elaborate enough to understand after making mistakes. So I had to ask my father who's extremely good at maths many times, for explanations. Without hi help I might not have been able to understand as well. Need improvement.

By Zax

Apr 13, 2021

This class fluctuates between impossibly hard, because a lack of instruction and examples were provided and too simple, because the same question is asked repeatedly. There is also very little mention of machine learning, despite the name of the specialization/course. That said, it was still the best survey course of the linear algebra concepts most relevant to machine learning.

By Ali R A

May 10, 2020

The course starts off well enough, but by week 4 the intuition for certain concepts is not imparted well at all, and the correspondence between notation from the lectures and that used in the practice quizzes breaks down badly.

I gave it 3 stars instead of 2 stars because the geometric intuition that is imparted is quite good, even though at times the notation is sloppy!

By Nate C

Jan 26, 2019

Having no background in linear Algebra made it difficult to complete the quizzes, assignments and exams. Even with the instruction (which was good) I found the hands on portions to be different from what was being explained in the videos. I will instead have to take the key concepts and do more research on my own to fully understand them.

By Fernando B d M

May 14, 2018

Like most of Coursera's courses there are no staff members available in the forums (which is extremely shameful for Coursera - repeating the same boring pattern over the years). Don't even try it if you have never seen linear algebra or python before. Otherwise, it's useful for practicing a few concepts or refreshing others.

By Mattia P

Mar 30, 2018

Nice course, with many insights. Sometimes the topics are given too quickly, I would have rather preferred less arguments but discussed more thoroughly. Nevertheless, I think this is a good one, especially if you've already got some background and you're looking for some general content to build upon it using academic books.

By Huy T

Jun 17, 2021

Overall, I learned some new stuff in this course. The programming exercises were interesting. However, the instructors really should provide more explanations regarding the calculations, formulas, and exercises' instructions and feedbacks. In many occasions, I had to looked up explanations online to solve the homework.

By Ana I P

May 7, 2020

Very challenging and interesting. However, the last module was a bit confussing and needed to look for materials on the Internet to really grasp a bit of understanding on the subject. Although sometimes frustrating, I think it is a good start to recap mathematics with a very practical approach.

By Faye M

Jan 16, 2020

Overall, it was a good summary to understand linear algebra. To get into the topic, I had to read through additional material as the videos and tasks provided in this course were a little shallow to my liking. I, personally would have liked more applicable machine learning examples.

By Ilaria G

Oct 24, 2019

I believe that the programming required in the assignments are not beginner level. I had never coded on Python before and I thought that there wasn't enough support on how to test my code before submitting, for example. On the other hand, the math topics were really interesting.

By Thomas S

Oct 16, 2020

I give this a three because the course focuses on themes with a macro lens while not giving the microdetails much explanation. Good foundation and interesting topic, but it seems counterintuitive for me to have to supplement the lectures with youtube lectures...

By Chakravarthy R

Sep 16, 2019

It was too fast for me. I answered many questions just by chance. But i got an overview of the concepts like diagonalisation , inverse, transpose, basis, span , eigen and so on. I am hoping that i will build on this.

By POR M H

Feb 1, 2020

I am feeling like something is missing during the last part of the course when it comes to Page Rank Algorithm. There should be more explanation to how the math works or comes to its formula.

By Santiago R R

Jun 20, 2020

The assignments kill this course, great instructors, and pace, in my opinion. (I am a beginner in linear algebra and I understood the concepts without needing Google or external resources)

By Rong D

Aug 30, 2018

I think the course is more suitable for those who have had comprehensive theoretical knowledge in linear algebra and intend to learn more about its practical use and its relevance to code.

By Marcus V C A

May 23, 2021

The course is good. But the last module (week) is not so good. I think that the explanation of the Page Rank algorithm is not very good. I also think that the final test is very confuse.

By TirupathiRao p

May 16, 2020

Overall course was good, I have learnt few new concepts which I haven't know till now. But at the end, things were not clear while putting all together for solving page rank algorithm.

By David D

Aug 18, 2020

Linear Algebra content is great, however, was not aware that a huge portion of grade is based on Python programming exercises!!! Only need to learn Linear Algebra, not programming!!!