If you are looking for the official code companion to GANs in Action: Deep Learning with Generative Adversarial Networks

: Another comprehensive implementation in PyTorch, tested on Google Colab, can be found at JungWoo-Chae/GANs-in-action 📖 Accessing the PDF

Key Features of the Book:

  • Intuitive Explanations: It breaks down the adversarial concept (a forger vs. an art detective) without requiring a PhD in mathematics.
  • Hands-on Code: Each chapter introduces a new GAN variant (DCGAN, CycleGAN, Conditional GAN) with executable code.
  • Real-world Use Cases: The book covers semantic inpainting, image super-resolution, and text-to-image synthesis.

While Manning Publications offers the official eBook and PDF, some users search for community-hosted versions.