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License: MIT No Attribution
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chrisbook's Introduction
- Chapter 1 - Generative AI Use Cases, Fundamentals, Project Lifecycle
- Chapter 2 - Prompt Engineering and In-Context Learning
- Chapter 3 - Large-Language Foundation Models
- Chapter 4 - Quantization and Distributed Computing
- Chapter 5 - Fine-Tuning and Evaluation
- Chapter 6 - Parameter-efficient Fine Tuning (PEFT)
- Chapter 7 - Fine-tuning using Reinforcement Learning with RLHF
- Chapter 8 - Optimize and Deploy Generative AI Applications
- Chapter 9 - Retrieval Augmented Generation (RAG) and Agents
- Chapter 10 - Multimodal Foundation Models
- Chapter 11 - Controlled Generation and Fine-Tuning with Stable Diffusion
- Chapter 12 - Amazon Bedrock Managed Service for Generative AI
chrisbook's People
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