about this book
Knowledge Graphs and LLMs in Action is a comprehensive guide to building hybrid intelligent systems that combine the structured reasoning capabilities of knowledge graphs (KGs) with the natural language understanding of large language models (LLMs). This book demonstrates how these complementary technologies can work together to create more powerful, reliable, and explainable AI solutions that address real-world challenges across various domains.
Who should read this book
This book is designed for machine learning engineers, data scientists, graph experts, and AI engineers who want to harness the synergistic power of KGs and LLMs. Whether you're working with structured enterprise data, building recommendation systems, developing fraud detection algorithms, or creating question-answering applications, this book will show you how to use both technologies to achieve better results than either could deliver alone.
If you're a data scientist looking to enhance your models with structured knowledge, a machine learning engineer seeking to reduce hallucinations in LLM applications, or an AI practitioner interested in building explainable and verifiable systems, this book provides the practical guidance you need. Although some familiarity with machine learning concepts and graph databases is helpful, the book introduces all necessary concepts and builds complexity gradually.