What Are GANs - Generative Adversarial Networks Explained

Explore the world of Generative Adversarial Networks (GANs) in this comprehensive 29-minute video tutorial. Learn about the fundamental concepts of generative models, the inner workings of GANs, and their training process. Dive into topics such as the distinction between generators and discriminators, the adversarial training framework, and the equilibrium state of GAN models. Discover various applications of GANs, including photo manipulation, face editing, text-to-image translation, and super-resolution techniques. Gain insights into the loss functions used in GAN training, including the minimax loss function, and understand how GANs generate fake data and handle classification errors. By the end of this tutorial, acquire a solid foundation in GANs and their potential in artificial intelligence and deep learning applications.

Intro
Photo to Emoji
Face Editing
Face Aging
Text to Image Translation
Photo Editing
Face Reconstruction
Fake Faces
Super Resolution
Derailing
Rosebud AI
GAN Networks
Generative Models
Discriminative Models
Generative Model
Discriminator
Initial Epoch
Output
Main Motive
Conclusion
Loss Functions
Fake Data
Classification Error
Loss Function
Minimax Loss Function