Generative Adversarial Networks (GANs) are a remarkable advancement in artificial intelligence (AI) that can produce images, sounds, and movies that are identical to the "real thing."
GANs learn quickly to create photorealistic faces and other media items by competing against two neural networks, one to create fakes and one to detect them. GANs are a major advance in deep learning systems, with the ability to produce startling deepfakes or amazingly lifelike animations.
One of the most significant advancements in deep learning, generative adversarial networks, is taught to you in this book. While learning about the generator and discriminator networks, the cornerstone of the GAN architecture, you'll discover how to begin developing your own straightforward adversarial system.
- Building your first GAN
- Handling the progressive growth of GANs
- Practical applications of GANs
- Troubleshooting your system
