About this document
GANs: Concepts and Real-World Uses by Khaja Riazuddin Nawaz Mohammed is a document available to read on EtoBox.
Generative Adversarial Networks (GANs) are a class of neural networks used in unsupervised machine learning to solve tasks like image generation. GANs work by having two neural networks, a generator and discriminator, compete against each other. The generator produces synthetic data and the discriminator evaluates it as real or fake. This adversarial training continues until the generator can produce data the discriminator cannot distinguish from real data. The document then provides examples of GAN applica
- Author
- Khaja Riazuddin Nawaz Mohammed
- Language
- EN