Generative Adversarial Networks (GANs) utilize two neural networks to create realistic data. Online courses offer in-depth training on GAN architecture, methods, and applications.
GANs are a powerful deep learning technique for generating realistic synthetic data. This course covers the core concepts of GANs, including the architecture of generator and discriminator networks. You'll delve into the adversarial training process, learn to implement GANs from scratch, and explore various applications beyond image generation. The course also addresses challenges like mode collapse and training instability, providing strategies for overcoming them. Finally, you'll gain insights into evaluating GAN performance and ethical considerations in GAN development. Numerical examples are provided on implementing GANs, including case studies on real-world applications and techniques for handling training challenges. Begin your journey into AI generation by enrolling today!