Awesome content and delivery! The visual illustrations and flow of the topics build very well on each other towards reinforcing intuition.

It is a great course that explains complex concepts in an easy and fun way. It is a great math refresher for those who want to learn ML. However, it feels like the last week of the course is too narrow and doesn't cover all the things you'd need to successfully pass the final quiz. For example I don't recall covering the relation between rank of a matrix and number of eigenvalues (and eigenvectors). The difference between eigenvector and eigenbasis. And how to determine the correct eigenbases if there is two of the same eigenvalues. I had to google it all on my own and I'm still not sure about the last one. Hope the community helps me.

Instructor has a great combination of subject knowledge and ability to explain topics in simplified manners. Each weeks topics were introduced in intuitive manner with good visualizations before diving into math. The visualizations in videos and quizzes were very useful. NumPy notebooks were structured in logical manner

Couple of suggestions for improvement - It would be useful to make slides for course available. Also the last week's core topics on eigenvalues and eigenvectors had very minimal video coverage and seemed rushed

The course structure is very good. For someone using it as a refresher as I have been it felt comfortable.

The only drawback I felt is that some assignments in the programming sections are not clearly defined about the output expected or process to be followed and got a couple of unexpected errors.

It is a great introductory course to linear algebra, but it misses some fundamental steps to better understand and use the tools taught. Labs are guided but the naming does not match that of the course. Some more exercises and examples should be provided for each lesson. Integrated with some of 3b1b's outstanding courses it will give you a great understanding of the subject and the ability to take one more step in becoming an ML engineer.

A lot of the math formulas are brushed over and almost as if the instructor assumes you already know how to solve the problems. There isn't a lot of content on the "how". How does the instructor calculate transformations, eigenvalues, etc. None of this is taught - it's just shown more like a result.

User beware - course programming exercises are structured quite poorly. First graded exercise (Gaussian Elimination) is puzzling in its design where it is (1) difficult to follow the logic of the function (different ways of doing reduced row echelon form) and (2) very difficult to trouble shoot what is going wrong given it is set up as a compound function. Not a newbie to programming or matrix math, so I wouldn't chalk it down to this. It's a shame as the course curriculum and structure is otherwise quite interesting.

After almost 2 weeks, I found that linkages to ML are weak and unclear (of course, there may be some. but I expect the instructor should demonstrate more) and Python programming projects are (and will be) coming out of the blue so I can't continue. Very disappointed.

Could have just mentioned it as linear algebra. Very few cases where ML is involved in the lectures. A few good youtube videos could have done the same job in even less time. Waste of money.

Quite useless course. Teachess really really basic concepts. There are no details. All excersies are designed as a simple plugging in of numbers.

Waste of time. Can be used only as a refresher course

A pure and concise intuition builder! I am on the younger side (14 years of age) and I adapt to concepts REALLY well if given the right direction. Not only this course but specialization is the pure definition of that!

Very visual and application oriented and gives the context for machine learning and where linAL is applied in PCA and neural networks. The structure is really byte sized and fun to work with.

This course is truly exceptional for individuals eager to strengthen their grasp of Linear Algebra concepts, paving the way for a deeper understanding of machine learning and data science.

The course and instructor were awesome. Added to that the course materials have been provided without any problem.

Graphic and simple approach that helps to understand fundamental concepts that are often not easy to understand

Great course. Looking forward to the next chapter in this specialisation.

I now understand the mathematics underlying machine learning.

You have a clear expression Luis ... We appreciate you

Good Explanation for Basic Linear Algebra concepts

Loved it. So many old memories refreshed

it was an amazing course.

thanks

A great great Course!

So interesting.

Perfect!