great course, only teaching what's needed, doesn't push you a lot in the coding assignments, as much as it requires you much more work to understand the codes and the science behind it.
Excellent course. The videos were a pleasure to watch, the assignments were clear and allowed you to go as shallow or as in depth as you desired, and the mentors were very helpful.
By Muhammed A Ç•
I liked the way instructor gives lectures but one problem is unfortunately she is not explaining things widely . Another problem is programming exercises. The problem is that you cannot print your code without writing it in true way which makes really hard to debug your code. Assertion codes are not informative. And there is not a expected result info as in other courses.
By Gustavo J M•
No se condice la pretendida profundidad de las explicaciones con las prácticas en código. Preferiría ir de a poco y más lentamente y dejar más claros los conceptos clave. La instructora es muy amable pero la velocidad del inglés es imposible de seguir para quienes no somos nativos.
By Henrik S•
The overview of several types of GAN with their potential issues that may arise, was good.
However, I would like to see the mentors more active in the discussion groups. I still have questions, that would have been answered quite easily by the mentors. That would have been great.
By Andrea B•
The theoretical concepts are explained in a clear way, even if I would have liked a deeper dive into the math behind the loss functions of each model proposed, moreover the assignments were too guided imo.
Nice course overall!
By Quarup B•
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.
By Aaron S•
Basically good, however the programming assignments are incredibly trivial compared to other machine learning courses I've taken on Coursera.
be unfamiliar with english and unlike Andrew use mathematical formula ， so i learn a little hard
By Michael K•
Great intuitive explanations but it is too easy
By Christoffer M•
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.
By Yu G•
Homework size are TOO large! One star given. One additional for that this course is highly challenging.
By Daniel J•
The content is clear but lacks any real depth. Any time a more difficult topic pops up the details are completely ignored or swept under the rug without any acknowledgement. Even a comment like "this topic is beyond the scope of what we want to cover here, go to this resource to learn more..." would have been far preferable. This seems to be a recurring theme in recent specialisations by deeplearning.ai rather than the fault of this particular instructor.
By Ranga R S•
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
By Michael S•
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