If you have completed all of the exercises in the chapters of this book, you have come a long way in your quest to learn and code Generative adversarial networks (GANs) for various real-world applications. GANs have the potential to cause disruption in a number of different industries. Scientists and researchers have developed various GANs that can be used to build commercial applications. Throughout this book, we have explored and implemented some of the most famous GAN architectures.
So, let's recap what we have learned thus far:
- We started with a gentle introduction to GANs, and learned various important concepts.
- We then explored a 3D-GAN, which is a type of GAN than can generate 3D images. We trained the 3D-GAN to generate 3D models of real-world objects such as an airplane or a table.
- In the third chapter, we explored conditional GANs...