فهرست مطالب

• Cover
• Copyright
• Table of Contents
• Preface
• Chapter 1. Introduction to Building AI Applications with Foundation Models
• The Rise of AI Engineering
• Foundation Model Use Cases
• Planning AI Applications
• The AI Engineering Stack
• Summary
• Chapter 2. Understanding Foundation Models
• Training Data
• Modeling
• Post-Training
• Sampling
• Summary
• Chapter 3. Evaluation Methodology
• Challenges of Evaluating Foundation Models
• Understanding Language Modeling Metrics
• Exact Evaluation
• AI as a Judge
• Ranking Models with Comparative Evaluation
• Summary
• Chapter 4. Evaluate AI Systems
• Evaluation Criteria
• Model Selection
• Design Your Evaluation Pipeline
• Summary
• Chapter 5. Prompt Engineering
• Introduction to Prompting
• Prompt Engineering Best Practices
• Defensive Prompt Engineering
• Summary
• Chapter 6. RAG and Agents
• RAG
• Agents
• Memory
• Summary
• Chapter 7. Finetuning
• Finetuning Overview
• When to Finetune
• Memory Bottlenecks
• Finetuning Techniques
• Summary
• Chapter 8. Dataset Engineering
• Data Curation
• Data Augmentation and Synthesis
• Data Processing
• Summary
• Chapter 9. Inference Optimization
• Understanding Inference Optimization
• Inference Optimization
• Summary
• Chapter 10. AI Engineering Architecture and User Feedback
• AI Engineering Architecture
• User Feedback
• Summary
• Epilogue
• Index
• About the Author
• Colophon