SKU/Artículo: AMZ-B0FZYLR44R
Graph in Action: Design, Build and Deploy Knowledge Graphs Using RDF, OWL, Graph Databases and Graph-RAG for AI-Driven Systems
Format:
Kindle
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Fuera de stock
Fuera de stock
Peso con empaque:
0.15 kg
0.15 kg
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Sí
Sí
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Nuevo
Nuevo
Producto de:
Amazon
Amazon
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USA
USA
Sobre este producto
- Unlock the Power of Knowledge Graphs to Build Smarter, Explainable, AI-Driven SystemsGraph in Action is a complete, engineering-focused guide to designing, building, and deploying real-world knowledge graph systems bridging semantic technologies with modern AI, large language models (LLMs), and Graph-RAG techniques.Whether you are a data engineer, AI architect, software developer, or technical leader, this book helps you move beyond traditional databases and unlock the true value of connected data, reasoning, and machine intelligence.What You’ll Learn Inside This Book✔ The fundamentals of knowledge graphs — RDF, OWL, SPARQL, ontology design, and how they enable machines to understand meaning not just store data. ✔ Building semantic data models — how to create ontologies, define relationships, validate data with SHACL, and model complex real-world domains. ✔ Working with graph databases — practical implementation using Neo4j, GraphDB, Amazon Neptune, and how to query using SPARQL and Cypher. ✔ Integrating data from anywhere — relational databases, APIs, CSVs, unstructured text, and real-time data pipelines. ✔ Reasoning and inference — how machines learn new facts automatically using OWL reasoners, rule engines, and semantic enrichment. ✔ Graph-RAG and LLM integration — how to connect knowledge graphs with large language models to provide accurate, explainable, and context-aware AI answers. ✔ Semantic search and explainable AI — combining vector embeddings with graph queries for hybrid retrieval and trustworthy AI systems. ✔ Deploying and scaling in production — using Docker, Kubernetes, GraphQL APIs, security best practices, data governance, and monitoring strategies. ✔ Real-world case studies — knowledge graphs in business intelligence, healthcare, finance, education, and enterprise AI.Who Is This Book For?This book is written for:Data Scientists, AI/ML Engineers, and NLP ResearchersBackend Engineers and Software ArchitectsKnowledge Engineers and Ontology DesignersEnterprise Architects and CTOs building intelligent platformsAnyone who wants to build explainable, scalable AI with real knowledge not just predictionsUnlike theory-heavy books, Graph in Action is practical, implementation-focused, and aligned with modern AI systems. You won’t just learn concepts you’ll build real graph-based systems and connect them to LLMs using Graph-RAG, Neo4j, SPARQL, and Python-based pipelines.Every chapter includes clear explanations, real examples, and ready-to-use templates.Take the Next Step—Build AI That Truly UnderstandsKnowledge graphs are the foundation of explainable AI, personalized search, intelligent assistants, and enterprise data intelligence. If you want to stay ahead in the age of intelligent systems this book is your blueprint.Get your copy now and start designing AI systems that think in connections, not tables.
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