Generative AI From start to surrender

Master the mathematical concepts behind generative models.

Deep dive into energy-based modeling approaches.

Study cutting-edge generative models and architectures.

Explore the mathematical foundations of diffusion models and their applications in generative AI.

From original GAN to StyleGAN: The evolution of generative adversarial networks and their capabilities.

Understanding variational autoencoders and their probabilistic approach to generative modeling.

Deep dive into the Stable Diffusion family of models and their state-of-the-art capabilities.