Table of Contents

  1. Introduction to Deep Learning
  2. Neural Networks and Deep Learning Architectures 
  3. Unveiling Generative Models
  4. Generative Adversarial Networks
  5. Variational Autoencoders
  6. Diffusion Models
  7. Transformers and Large Language Models
  8. Exploring Generative Models
  9. Video and Music Generation
  10. Artistic Side of Generative AI
  11. Ethics, Challenges, and Future