Hands-on examples for image-to-image translation, high-resolution image generation, and targeted data generation. Alternative GitHub Resources

Beyond the official repository, the developer community has created several valuable forks and adaptations:

Learning pro tips for troubleshooting and making your systems smart and fast.

The book is structured to take you from a beginner to an advanced practitioner:

A public PDF version can sometimes be found in community curated lists like the Books/GANs.pdf file on GitHub.

For those who want to run code in the cloud without local setup, JungWoo-Chae's repo provides PyTorch implementations optimized for Google Colaboratory. Accessing the PDF

Understanding the "game theory" competition between the Generator and Discriminator .

If you prefer PyTorch over TensorFlow, stante/gans-in-action-pytorch offers idiomatic PyTorch versions of the book's examples, including DCGAN and CGAN.