I really liked the exposure to preparing various loss functions in paired and non-paired GANs, introduction to other applications, and many great changes to improve the quality of the networks!
GANs are awesome, solving many real-world problems. Especially unsupervised things are cool. Instructors are great and to the point regarding theoretical and practical aspects. Thankyou!
par Stanislav K•
The course material is of very good quality. On the other hand, most of the coding exercises are limited to implementation of the loss functions. They are not teaching the students how to design the GAN architectures yourself.
par Rishab K•
Very good course, assignment could be made more longer than what is currently here. Should also include a project at the end to implement GAN
par Aditya S•
Great course by a great instructor and great team behind! Learned sooooo damn much. Can't wait to go out and apply some of this stuff!
par Artod d•
Not very well structured course. I think there is some room for improvements.
par Ibrahim G•
The assignments can go more in depth, but the content was great!
par Keebeom Y•
For English subtitles, there are many typos and sync of video and subtitles don’t match in some parts. Lecturer speaks too fast. But the content was very good, specifically coding projects.
par Mark P•
The programming assignments are too easy. Although the linked papers were useful I felt the optional notebooks should have been compulsory or we should have had to do more ourselves.
par Sameer R•
Too much repetition. More technical aspects could have been covered, given this is third course.
par Liang Y•
The Instructor did a great job on scripts and PPTs. However, Instead of teaching you GANs, she reads the scripts in a super fast speed. It is good that if you are reporting or interviewing since your audiences are professors or specialists who are already very familiar with GANs. But I think most of the audiences here know little about GANs. I prefer Andrew Ng's teaching style which guides the audiences and gives them time to think and learn.
par Farhad D•
Exercises were so bad. They are very easy, and they are ambiguous a little bit. It seems the creators got tired at the end and they did a bad job. However, I learned a lot and I am thankful, but It could be much better!