Informative, but it feels like it didn't include explanations (or at least intuitions) required to fully grasp the concepts. For example, the necessity of 1L continuity and why does the enforcement work.

The videos teaches GAN, which is great, but the lab train for pytorch, which is great as well. But I wish the video and the lab works together so we can apply what we learn from the video into labs.

Very interesting and comprehensive courses, but more complex skill are in optional modules, perhaps these very interesting and intricate skills are for nex modules? Good course!

The programming assignments can be improved by designing it in such a way that most of the work should be done learner not by the course designer. I hope you change it in future.

Basically good, however the programming assignments are incredibly trivial compared to other machine learning courses I've taken on Coursera.

I would have liked to have more theoretical details on the mathematical point of view of the topics covered by this course

I don't know what the instructor is hurrying about. In terms of clarity, she is not even close to Andrew.

be unfamiliar with english and unlike Andrew use mathematical formula ， so i learn a little hard

Can be more detail. In week 3 and 4, there is not much information shared/taught.

I don't like the style of programming assignments, otherwise good

Great intuitive explanations but it is too easy

She talks too fast! Please slow down!

The GANs in the course are basic as advertised, but unfortunately the treatment of the theory is basic and shallow as well. The lab assignments are too simplistic to force any deeper understanding.

The assignment on the week 3 didn't compile. Probably some version mismatch issue.

The instructor didn't go into the details of the some of the key concept, they kept it very vague

The course if very interesting, but unfortunately after the completion you lose the access to assignments and the only way to restore it is to subscribe again.

It was too high level without mentioning the math behind the theories. The codes were too simple and not challenging. The instructor was speaking too fast.

Homework size are TOO large! One star given. One additional for that this course is highly challenging.

Not much value in auditing this class w/o access to the coursework itself.

After week 1, not sure what the objective of this course is, seems this is more about PyTorch.

The course material about the concept of GANs is actually quite good, but the assignments are near impossible for me as I am not a PyTorch expert. Trying to figure out the syntax, not really what I was looking for.

A couple of years back, I completed one of their earlier courses (Machine Learning) and it didn’t use any language, but essentially a MatLab like environment to manipulate matrices and vectors.

No sweat, I’ll just cancel the subscription and find another way to learn this stuff.

Had to pause multiple times to listen again or read the English translation at the bottom. Slowing down the lecture along with proper pauses and meaningful visual illustrations can improve this course in a big way.

Content of this course is good, but the way it is presented leaves much to be desired

The coding exercises seem completely unguided by the course, and feel like a waste of my time.

I'm not going to pay you for the time I spend studying pytorch.org

thanks for the hard work, but I feel a lot of places not explained clearly, and the assignment is also not that helpful

how can i create my first GAN without guidence.

Way, way, way too light on the details