Generative AI notes - Advanced

Content Structure (13 Main Sections):

1. Introduction to Generative AI
2. Fundamental Concepts
3. Mathematical Foundations
4. Types of Generative Models
5. GANs (Generative Adversarial Networks)
6. VAEs (Variational Autoencoders)
7. Transformer Models
8. Diffusion Models
9. Large Language Models (LLMs)
10. Applications and Use Cases
11. Practical Examples and Automation (10+ complete code examples)
12. Ethics and Challenges
13. Quick Reference Guide (formulas, tips, debugging)