Overall the course was very informative and learned much on it but, if I had any remarks to give it would be the following and only related to Week 4: (Week 4 issues) - Course still needs to become more detailed when It came to solving matrices and equations - Eigenvalues and Eigenvectors need to be very much more detailed, also need to check more on the quadratics Programming assignment (Week 4): - Understanding shear / y-axis projections was complex - Understanding Discrete Dynamical System was quite complex

There is a beauty to this course that sometimes gets lost in the frustration of doing the labs. I have been working with python for years, and still got pretty frustrated in the challenge labs. So aside from the course, I would like the team to please add some videos or documentation for basic python, and specially, the various numpy functions. One notebook containing all the Numpy tricks and tips will be an invaluable reference!

Bad:

Horrible - Very elementary course - did not learn much..

Strange accent with very inferior & buggy transcriptions..

Volume very low..

Good:

The style of teaching was very intuitive, and the Instructor Luis seems quite creative!

Luis, put in the effort to make this better.. last quiz demanded lots of donkey work..

(How not to create a lousy course..)

The only good part is that the Author is creative & enthusiastic..!

Thank you.

Good course to refresh the basics. At some points, the intermediate questions in the videos come too quickly. In the case of eigenvalues and eigenvectors, I actually miss a bit more content or a better explanation. 2x2 matrices are nice to explain, but I would like to see further content at this point. This is even in the video on "Eigenvalues and eigenvectors", but from my point of view it comes much too late.

The course was well designed and structured. The assignment had a few bugs that I have reported in the community and hope that it will be fixed soon for new students who will be taking this course to transform their academic and professional lives in the future. And thanks to all the people who had contributed to this course and a special thank to Andrew Ng and Luis Serrano for this wonderful course.

I wanted to like this course more. Serrano is an excellent teacher, I loved the visual style, but I wanted to go deeper on this topic. I understand that it was geared for beginners; as a practicing data scientist, however, I would have benefitted from a deeper treatment. So, I hope that prof. Serrano will consider a follow up course at the intermediate or advanced level.

A good introductory course, providing the idea of how linear algebra is used in machine learning. I'd rather watch along with 3blue1brown youtube course on linear algebra to get solid understanding. Personally, would like to see a better explanation of the use eigenvectors related to the dynamic states (the last exercise) and some material on single value decomposition.

The Syllabus, learning material visualization, additional tools, labs, everthing is solid 10/10. but im having hard time to understan the way the luis talk, honestly, the way he talks is too fast for me, and the conjunction word such as "of", "and", "is", etc, are not pronounced clearly. that's why i need to watch the video repeatly and sometimes on slower speed.

Earlier I completed this course and it contained only the Mathematical concepts But now as the course is updated, it takes first Machine Learning application, introduces the mathematical concept to be used for that case and delves deeper into Mathematical concepts. I hope so that such changes are made to other remaining parts too.

It is a great course, but I don't feel enough comfortable with my level in Linear algebra, I learned a lot about linear equations, matrices and machine learning. But I'm not sure if I could understand how machine learning algorithms works. But this course is an excellent introduction to find more information about Linear algebra.

The material is well thought out but the examples are not that great, The instructor tends to use colloquialisms which is fine but sometimes hard to follow. The examples could be more thorough and step by step. A number of times they move from one matrix to another transformation but its actually multiple steps condensed.

An excellent coverage of Linear Algebra with very good hands on assignments to make the concepts sink in. I do believe that the lectures can be improved a bit more especially for the more complex topics with more examples to work through. I had to refer other lectures and videos to really understand many of these topics.

A mostly good, thorough and intuitive introduction to linear algebra. Unfortunately, had to rely on some other resources to complete assignments in week 4 as explanations seemed to be insufficient (maybe just me). Plus, programming assignments used notations that hadn't been discussed previously.

Very strong 4/5.

I already know about Linear Algebra, but this course brings me another perspective and shows me the application of Linear Algebra to Machine Learning, a field in which I have a special interest. This course does not provide me with new concepts, but it does consolidate my knowledge and bring me tools to use it.

A very good course for any beginner, gives you a good overview of the essential concepts with profound practice. I would recommend to add more content on how a particular concept is used in ML. Eigen vector section can be improved. Overall, perfect to learn Linear Algebra for Machine Learning and Data Science.

I enjoyed the course, but felt the last lectures on eigenvalues, etc. could have been expanded on a bit. The coding lab had some good exercises, but the instructions on pagerank application exercise were confusing: it seemed like there were constraints on the values for the P matrix beyond those specified.

Pretty good overview of linear algrebra and its applicability to machine learning. However, I found the explanation to Eigenvalues and Eigenvectors to be unclear. The content could be improved by making it clearer how one progresses from finding Eigenvalues to finding and chosing Eigenvectors.

It is expected that you will be doing a lot of research or already have linear algebra knowledge and want to refresh your memory or do some programming-oriented algebra. Since I am studying linear algebra for the first time, I intend to take another course to enhance my knowledge of the subject

It is really good introductory course, refreshes all your basics of linear algebra. I had to unlearn some of prejudices in order to understand the concepts clearly. I expected a little more deep dive like Markov matrices applications, being said that it is really helpful.

دورة ممتازة لمن لديهم خلفية عن الجبر, وُضِح فيها علاقة الجبر بتعلم الآلة وكيفية تسخير مفاهيمه لها وومالهدف منها, توضيح سلس ورائع, لكن الدورة ناقصها تطبيق عملي, فلا يكفي الاكتفاء بها. لكن بشكل عام كمقدمة لاستخدامات الجبر في مجال تعلم الآلة فهي وافية ومتميزة في هذا.

Course material was interesting and most of it was easy to follow. The section on Eigenvectors and Eigenvalues could have been much better explained. The examples skipped steps, and could have been more thorough. I had to do a lot of reading on my own.

The teaching is very good, assignments and labs helped me to gain more information and practice. But, some of the lectures could have been taught better in more simple terms and with some more good examples. Overall I had enjoyed learning with this course!

Course is good, but it is not for beginner for sure as you must need prior at least intermediate level experience. If you are starting fresh and do not remember linear algebra from schooling i would suggest not to take this course before reading about it.

A good course that explains the concepts of linear algebra in an understandable manner. There were certain modules that I had some trouble understanding but pairing this course up with some research of my own and 3b1b's youtube playlist was very helpful.

The course was absolutely rewarding , Mr Serrano explained and covered it well.

But I noticed there were a few details that he forgot to mention that I went searching for on google.

Otherwise,I really liked this course and I actually learnt many things!!