The Neo4j AI Blueprint: Building Intelligent Applications with Graph Databases, Machine Learning, and Generative AI

Author:   John Sanders
Publisher:   Independently Published
ISBN:  

9798243392075


Pages:   228
Publication Date:   10 January 2026
Format:   Paperback
Availability:   Available To Order   Availability explained
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The Neo4j AI Blueprint: Building Intelligent Applications with Graph Databases, Machine Learning, and Generative AI


Overview

Build intelligent AI systems powered by relationships, context, and explainable reasoning. The Neo4j AI Blueprint is a comprehensive, hands-on guide for developers who want to build modern AI applications using graph databases, machine learning, and generative AI. As AI systems become more complex, traditional data models fall short in capturing relationships, dependencies, and real-world context. This book shows how Neo4j solves that problem by making relationships first-class citizens in your AI architecture. Starting with the fundamentals of graph databases and the Cypher query language, you'll learn how to model data specifically for AI use cases. You'll then explore graph algorithms, feature engineering, and machine learning workflows that unlock insights impossible to achieve with tabular data alone. Each concept is explained clearly and reinforced with practical, runnable examples designed for real developers-not academic theory. As the book progresses, you'll dive into advanced AI architectures, including knowledge graphs, vector search, Retrieval-Augmented Generation (RAG), and integrations with large language models. You'll learn how Neo4j acts as a structured memory layer for generative AI, grounding LLM responses in trusted, explainable data while reducing hallucinations. Unlike many AI books that stop at experimentation, The Neo4j AI Blueprint takes you all the way to production. You'll learn how to scale Neo4j for AI workloads, optimize performance, secure and govern graph data, and design explainable AI systems that meet enterprise and regulatory expectations. Advanced chapters cover Graph Neural Networks, hybrid symbolic-neural reasoning, and future-ready graph AI patterns. Written in a clear, developer-focused style, this book teaches through action. Every example is complete, correct, and designed to be applied immediately. Whether you are building recommendation systems, intelligent search, knowledge-driven AI, or real-time decision engines, this book provides the blueprint. If you want to build AI systems that understand relationships-not just data-this book is for you

Full Product Details

Author:   John Sanders
Publisher:   Independently Published
Imprint:   Independently Published
Dimensions:   Width: 17.80cm , Height: 1.20cm , Length: 25.40cm
Weight:   0.404kg
ISBN:  

9798243392075


Pages:   228
Publication Date:   10 January 2026
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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