WARNING: This course is NOT for beginners. The requirement description is not true

Videos: This course is taught in a very dense way and fast that beginners may not be able to catch up. I saw many people in discussion forum complained about this.

Programming assignments: They are NOT for beginners too, assignments are not that something you can understand right away without basic coding knowledge (loop, else if, function, variable). If you don't know any of these, consider learning elsewhere before study this.

I'd recommend this course to those who already have fundamental knowledge in Linear Algebra or those want to revisit after time. The Lecturers taught Linear Algebra in both geometrical and algebra view, which help you understand better.

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!

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)

This course is absolutely stunning in terms of explaining mathematical concepts. I personally have been out of hands-on touch with mathematics for a decade, and by going through these videos, tutor has been absolutely spot on for me in bringing back my mathematical memories. Would highly recommend this course for anyone wanting to enhance their mathematical skills or brush up on mathematical concepts before doing deep dive in machine learning concepts. It really connects and I am enjoying this. Thanks for all these wonderful lectures.

I found the course very interesting and useful. I really liked the approach of relating Linear Algebra to practical use. Traditional approach to teach Linear Algebra (which assumes some familiarity with Modern Algebra) may not be for everyone and the approach taken in the course will find much acceptance among curious learners. Thank you so much for putting this course together. May be, putting together a more detailed and longer course on Linear Algebra will be good idea - if it happens, i will be the first one to enroll !

I have tried Linear Algebra via Gilbert Strang lectures before but found them unengaging because they are so abstracted. Here we see how the linear algebra applies directly to pageRank, which I found a cool example.

In general the questions allow for a good practice and build up, and I really appreciate the lecturers appreciation of the fact that hand-written calculus is becoming a thing of the past, and so we should focus on the big ideas behind the methods that are now so standardised for processing linear systems.]

Many thanks for David and Samuel! I've been struggling with linear algebra for quite a long time. I can do the math, but I get lost when I try to use linear algebra to understand something in statistics and machine learning. The intuition based approach is perfect. I like the apple-banana example, I like the transformation and visualization of eigenvector in 2 dimension. Also, the page rank case is quite cool and thought provoking.

I think I will stay on this series for following two courses.

Thanks again!

Best presentation of fundamental Linear Algebra I have ever seen, hands down. (I'm an old-timer, reviewing this material to get up to speed on Machine Learning and Data Science.) While teaching the mechanics, the concepts behind them are always reinforced. Thank you for presenting this material in such a meaningful and digestible way. I also greatly appreciate the reverse-transparent-whiteboard which to me is highly preferable to the other methods I have experienced in online courseware.

This is such a wonderful course. Two instructors explains complex concept with clarity and enthusiasm. They explained linear algebra from a different perspective. When I learned in college, I was taught to remember lots of definitions and concepts, but in this course, they teach you why we do certain steps not just how to do. However, I want to remind people who are interested in this course, it is not for beginner or who wants to learn linear algebra, instead of linear algebra for ML.

Excellent introduction. For me, as someone who had studied vectors and matrices at school, decades ago, it was wonderful to go back and re-learn this stuff in a different way. This course is much more focused on the meaning and usefulness of these things, rather than just learning how to do the maths. The first 3 minutes of the session on eigenvectors brilliantly showed in graphical form what they really are, something I'd never really grasped at school. Recommended.

An excellent breakdown of linear algebra and the tools and processes that it takes to perform these operations. The lectures give you a good understanding of the concepts of vectors, scalars, dot product, matrices, and eigenvalues and vectors. I would highly recommend this course for anyone who is needing to understand how linear algebra can be conducted via computers, while still grasping the underlying concepts that make one proficient at linear algebra.

I had previously taken linear algebra, but this was a good refresher. The pace of this course is quite fast for 5 weeks, and the course does not dive into any proofs. It may be useful to get some outside supplements to get through the materials. I really enjoyed the way that the concepts were explained and presented such as eignvalues/vectors. They help provide some intuition instead of simply presenting the formula or grinding through proofs.

This is a great course! Be advised: It is very challenging and will kick your butt if you haven't seen much linear algebra before. The content in the course won't always be enough to solve all of the assignments. But look into the forums and use some other sources and you will succeed in this course. Overall I am glad I took it even if it will take a little longer until I can say that I master everything that was covered in the course.

The perfect dosage of the key elements in linear algebra to mastering the concepts of machine learning. The course leaves you with a clear intuition for vectors and matrices and how these objects can be manipulated, and most importantly why these objects are fantastic. I am an immunologist with a little background in machine learning and my last studies in mathematics taken 15 years ago, but this course has the perfect level I need.

This course was like God-gifted.

I had just finished my 2nd sem at college(BTech) and we had Matrices in the syllabus so I knew how to calculate (just calculate -_-) eigenvalues, vectors and so on but I just saw them as numbers. At my college, we were not given such geometric insight and when I learned it through this course, MY GOD was I blown away.

I feel so lucky to have found this course! I learned A TON of stuff.

Thanks!!

I enjoy attending this course. I consider this course really good, mostly due to a lot of intuitive examples about particular subjects of study, explanations that were clear and enthusiastic professors. Finishing this course gave me motivation to learn more about machine learning and mathematics that it's based upon.

This course is great for those who want to understand the geometric meaning of linear algebra. Really loved the course videos and quizzes. Just one suggestion - Coding assignments should be bit more challenging as this course is targeted around ML, maybe some small Kaggle like project at the end of course.

Excellent, crisp and to the point. Instructors made the concepts way to easy to understand. Enjoyed my time learning from them and ofcourse relevant material was provided.

I think Professor David Dye's Linear Algebra video is the best course. It's much more clear, intuitive, and focused in the machine learning domain. I like it so much!!!

I started this lecture yesterday (3/4) and completed it today (3/5), and it's so nice to be able to know, use, and understand linear algebra in such a short time!

Good course. You need to know Matrices, some Algebra, vectors, Python and Maths beforehand to learn in this course, else you will end up frustrated and annoyed.

A good value, well organized, with many exercises for practice. Effectively uses visuals, and contains the occasional very creative example.

Some caveats

a) this course is not for the absolute beginner. You'll need secondary / high school math, and basic familiarity with python

b) understanding linear algebra at this level is a second year full semester course at university. So if you want to understand the concepts - rather than just get the certificate - be prepared to use outside resources and invest considerably more time than advertised. Some linear algebra topics are skipped (cross product), and others are not well integrated into the course (Einstein summation)

c) while linear algebra is central to understanding machine learning, there are very few machine learning applications in this course.

And finally a small annoyance: I wish the instructors would get out of the way of the whiteboard at the end, so I could get a screen capture.

Overall, a worthwhile course.

D

Overall a good course. But I think in order to get the most of this course, it would be better that you already had some knowledge of linear algebra. Then this course could give you some intuition. Put another way, this course is not for complete beginners in linear algebra. And the programming assignments are also good. Highly recommended!

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.

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.