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

Eigenvalue &Eigenvector, Matrix & Inverse Matrix, The Gram–Schmidt process, Page RanK.

I was weak in maths and my background was not that strong, But I learned here how to tackle with

wonderful lecture tutorials

I want to apply ML in my research in electric power system

What an excellent lecturer.

I just wish that my mathematics teacher at school had had a tenth of the ability to impart knowledge.

This is a fantastic course and I will be doing the specialization later when I get some free time.

Thank you for a fantastic course.

Dariusz

It feels a bit intimidating at first!

Then you realize that it was a while ago since you needed this part of the brain.

Things might seem simple in some videos, but trust me it pays off in the end!

The last part of this specialisation requires you to be on your toes!

This is an awesome course! You probably were like me, with a foundation in maths shaky due to poor understanding of the underlying principles. This course re-centers math around intuition, making it much easier to understand and apply the concepts with confidence.

I really like the approach of this course: build the intuition of the core concepts with an easy language and loads of examples. This has helped me a lot to understand finally the eigenvector and eigenvalues, for example. I strongly recommend to take this course.

This was one of the best courses I have ever had. The courses structure was awesome and the instructors were very clear with what they were teaching. The assignments were good. Anyone with a fair understanding of high school algebra should be able to understand.

It's been really fun, It broadens my view about linear algebra and its relation with machine learning. It also helped me a lot to understand the topic which was in my college course. My favorite part was the Gaussian elimination and the Gram-Schmidt Process.

I would like to say that this was one of the best courses that I've learned online during these difficult times of COVID-19 Pandemic. the teachers professor David Dye and Professor Samuel J Cooper were very friendly in teaching , all my concepts got cleared.

A really great course for building foundational intuition around linear algebra. Great for data folks who are used to applying libraries (e.g. scikit-learn, numpy, scipy), but want to gain a deeper understanding of what the methods are doing under the hood.

Superb course! One of the best I have taken. I already knew linear algebra, but you always find rich tips and different ways of understanding the main topics. Congratulations to both professors. It is quite visible the passion they have and try to share it.

An excellently simple explanation of concepts of linear algebra. Applause for lector. I really liked this course and found it very useful for those newbies in machine learning like myself. I recommend this course to all my friends and others interested in.

This course has an amazing way of teaching. So u understand the concepts of mathematics that was seeming harder to me before i applied for this course. If you are beginner at Machine learning and worried about mathematics you must go through this course.

This is one of the best courses I have seen in coursera. The material was good and instructors were excellent. The subject and topics were explained in a very simple and interesting manner making it very easy to understand and also fun at the same time.

I highly recommend this course to anyone who wants to build a general understanding of linear algebra and its real-world application. Both the instructors are highly capable of communicating the intuition behind every steps and algorithm to the viewers.

This was one of the best courses for linear algebra for a working professionals, students and researchers who want to brush up their skills as this course is very different from the regular book stuff.It was more practical with real world assignments.

Awesome course! Entertaining and digestible, with great assignments despite some hiccups in file organization and a slight lack of response from admins (understandable because the course is old). It was so awesome that I had to go and tweet the profs.

it's a very well structured and well taught course. The lecturers have the ability to keep the students interested in the subject and the various exercises at the end of each session are a very good way to find out where extra work/research is needed.

Clearly explained and key equations are derived with good step sizes. Quizzes and assignments are challenging (which is good!) and have high expectations for learners (which is really good for my motivation). Overall, I am really enjoying this course.

A really nice course, I had already done a Linear Algebra module in the university. But that was mostly mugging up and not knowing what this is used for. This course's geometric interpretation of all topics, helped me a lot and give a lot of insight.

The presentation an way of teaching is excellence; however, the course should add more reference or additional source or materials for more in dept detail for the person who feel that the simplified explanation in the course are still not sufficient.

So exhausted, but amazed how the computer managed to process this kind of things for us everyday!

The lecturer were so nice and the explanation was so clear and funny too, although there are several assignments (which on my opinion) is sooo hard :((

Extremely helpful. I haven't taken a linear algebra class in almost 5 years and by going through these videos it helped me regain an intuition towards the subject. The videos do a good job of tying the material back to machine learning as a whole.

Great maths refresher content, with very useful 2D geometrics examples helping to build the intuition rather than just explaining the maths. I feel like I can understand this part of linear algebra now, and I know what to search for when I won't.

Great explanation of all the important things, with topical examples and practical tasks. Still, it seemed to me that the course was growing more and more complex exponentially by the end of it, so it was really hard to catch up starting week 4.

The perfect class to either get introduced to the important parts of Linear Algebra or to brush up your skills. I would definitely suggest anyone take this course for the quality of the lectures, the delivery, and the fun programming exercises!