Generative AI with Python and Pytorch 2nd
Master GenAI techniques to create images and text using variational autoencoders (VAEs), generative adversarial networks (GANs), LSTMs, and large language models (LLMs).
- Implement real-world applications of LLMs and generative AI
- Fine-tune models with PEFT and LoRA to speed up training
- Expand your LLM toolbox with Retrieval Augmented Generation (RAG) techniques, LangChain, and LlamaIndex
- Purchase of the print or Kindle book includes a free eBook in PDF format
Table of Contents
Chapter 1: Introduction to Generative AI: Drawing Data from Models
Chapter 2: Building Blocks of Deep Neural Networks
Chapter 3: The Rise of Methods for Text Generation
Chapter 4: NLP 2.0: Using Transformers to Generate Text
Chapter 5: LLM Foundations
Chapter 6: Open-Source LLMs
Chapter 7: Prompt Engineering
Chapter 8: LLM Toolbox
Chapter 9: LLM Optimization Techniques
Chapter 10: Emerging Applications in Generative AI
Chapter 11: Neural Networks Using VAEs
Chapter 12: Image Generation with GANs
Chapter 13: Style Transfer with GANs
Chapter 14: Deepfakes with GANs
Chapter 15: Diffusion Models and AI Art
