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Computer Science
Artificial Intelligence
Generative AI
1. Introduction to Generative AI
2. Mathematical and Technical Foundations
3. Machine Learning Fundamentals
4. Core Generative Model Architectures
5. Transformer Architecture and Language Models
6. Text Generation Applications
7. Image and Visual Generation
8. Audio and Speech Generation
9. Development Lifecycle and Best Practices
10. Practical Implementation Tools
11. Ethical Considerations and Responsible AI
12. Legal and Regulatory Landscape
13. Economic and Social Impact
14. Future Directions and Emerging Trends
Image and Visual Generation
Image Synthesis Fundamentals
Pixel-Level Generation
Autoregressive Image Models
Convolutional Approaches
Latent Space Generation
VAE Image Generation
GAN Image Synthesis
Diffusion Image Models
Text-to-Image Generation
Multimodal Understanding
CLIP Architecture
Vision-Language Models
Conditioning Mechanisms
Cross-Attention Conditioning
Classifier Guidance
Classifier-Free Guidance
Popular Models
DALL-E Architecture
Stable Diffusion
Midjourney Approach
Imagen Model
Image Editing and Manipulation
Inpainting Techniques
Context-Aware Filling
Semantic Inpainting
Style Transfer
Neural Style Transfer
AdaIN Methods
Arbitrary Style Transfer
Image-to-Image Translation
Pix2Pix Framework
CycleGAN Approach
Unpaired Translation
Advanced Visual Generation
Super-Resolution
Single Image Super-Resolution
Real-World Super-Resolution
Video Generation
Frame Prediction
Text-to-Video Synthesis
Video Style Transfer
3D Generation
Neural Radiance Fields
3D Object Synthesis
Text-to-3D Generation
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6. Text Generation Applications
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8. Audio and Speech Generation