Learner Reviews & Feedback for Build Basic Generative Adversarial Networks (GANs) by DeepLearning.AI

As a beginner to GANs, this course offers a lot of new insights that I never came across before. It helped me understand a lot of the key terms used in current state of the art research papers and helped me understand a lot of the underlying working principles of GANs.

Thank you so much for providing this wonderful course. I've learned a lot from your wonderful lectures. Specifically, I really like the way you give your lecture, very concise and interesting. Thanks again, and hopefully a lot of people can enjoy the course as well.

The inclusion of unit tests and hints in the programming assignments are a huge "step up" from previous Coursera programming assignments. All Coursera classes should have used this model from the very beginning. Having said that, it's better late than never.

Excellent course. Explained in a very basic & understandable way for those who don't want to be complicated with too much mathematical background and still refers the participants to optional reading materials + active discussion in the course forums.

Well designed exercise, in which I only need to read thru and understand the key points, and the actual coding part is very minimum. Courses are well taught with enough readings and reference provided. Most of them are up to date in research frontier.

This course was awesome. All the concepts were up to point and all the detailed reading materials are provided. The notebook's configuration was perfect to train the model. Looking forward to the same experience in the next course.

Great explanation and great way to summarize huge topics but the assignments are really taking a huge time for training purpose if possible try to reduce the no.of epochs or provide a pre trained model and training the last layer

The course is very good.The video lectures were super cool to understand.I just felt that the assignments should be a little bit more difficult like it should be given to write most of the code rather than filling just some cells

Thanks much for the course. The contents are concise and optional material is called out separately. The speaker can slow down a bit as it's hard to keep pace understanding what she is saying and looking at the video contents.

Even though the lectures style is quite different from the previous deeplearning.ai courses (showing slides instead of explaining on a white-board), the Colabs made the understanding the concepts very visual and intuitive.

Very nice and informative introduction, even though it might be a bit difficult at times if you have never heard of concepts like "latent space" or "disentanglement" before :)

In all, really great work, thanks for this.

This course introduces concepts in a clear and simplified fashion and allows to have a hands on with basic GANs models. Further insight can be obtained through the recommended papers. I look forward to the next course

I have been trying to understand and implement GANs for que a few weeks and it felt really hard but after this course made everything easy for me, deeplearning.ai has been really one of the best places to learn.

It would be helpful to include the formula of the normalization in the last parts of the assignment, as reading through the instruction is fine but having the actual regularization formula available is helpful.

Wonderful course for anyone interested in getting an introduction to GANs. All this knowledge will help me get closer to do research on state-of-the-art GAN models. Thank you for creating this material.

Excellent course, the first good thing is using PyTorch, love it , never had work with this framework and its really nice, second thing is about GANs, amazing topic I really want to learn more about it!

Great introduction of GANs. I particularly liked the programming assignments' difficulty (not too easy and not too hard). Also, the instructor is usually very clear and didactic.

Excellent introduction to Generative Adversarial Networks (GANs). The course is easy to follow, and the assignments are challenging. Thanks for the great learning opportunity.

Very nice course to start your acquaintance with GANs. Loved the non-obvious mention of ProteinGANs to generate protein structures.

Definetly a recommendation for the novice.

The course is great with hands-on experiments. The assignments are properly designed to let the learner focus on the most important pieces of the logic in the implementation

The course is amazing with an amazing instructor. I really enjoyed the course and thank you so much for making this specialization. A big thanks to deeplearningai team.

Good overall introduction to GANs. I really liked how well the sections on Wasserstein Loss and Conditional & Controllable GAN sections were covered in this course.

This course was awesome. Concise, simple and straightforward. The course teaches something very sophisticated but the instructor made it very easy to understand.

Great course! The programming assignments were a bit short and too easy. The Deep Learning Specialization assignments had the ideal difficulty and length.

I really like the way he teaches all the concept from scratch. i learn a lot

any one want to learn foundation for GAN i really recommend them this course