Key Features
- Implement RAG’s traceable outputs, linking each response to its source document to build reliable multimodal conversational agents
- Deliver accurate generative AI models in pipelines integrating RAG, real-time human feedback improvements, and knowledge graphs
- Balance cost and performance between dynamic retrieval datasets and fine-tuning static data
Who this book is for
This book is ideal for data scientists, AI engineers, machine learning engineers, and MLOps engineers. If you are a solutions architect, software developer, product manager, or project manager looking to enhance the decision-making process of building RAG applications, then you’ll find this book useful.