A public PDF version can sometimes be found in community curated lists like the Books/GANs.pdf file on GitHub.
Fully functional code for every chapter, from basic GANs to advanced models like CycleGAN.
Exploring Progressive GANs, Semi-Supervised Learning, and Conditional GANs.