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Synopsis
Artificial intelligence is evolving—and so should the way we build it.
In a world driven by data, intelligence comes not just from the volume of information, but from the connections we can make between concepts. Knowledge graphs are at the forefront of this evolution, powering smarter AI systems that understand, reason, and adapt. From enterprise search to recommendation engines, from fraud detection to AI assistants, knowledge graphs enable machines to move from pattern recognition to true contextual understanding.
Knowledge Graph Mastery is the definitive guide for building intelligent, scalable AI systems grounded in structured, semantic knowledge. Whether you're a software developer, AI engineer, data scientist, architect, or researcher, this book equips you with the tools, concepts, and real-world examples you need to master the design and deployment of modern knowledge-driven applications.
This comprehensive, practical book takes you from foundational principles to advanced graph reasoning techniques. You’ll explore how to structure and interlink information, model domain-specific ontologies, query complex graphs efficiently, and integrate them with machine learning workflows.
Inside, you’ll learn how to:
- Understand graph theory and graph thinking as a foundation for AI
- Design semantic models using RDF, OWL, SHACL, and linked data principles
- Build and query scalable knowledge graphs using SPARQL, Cypher, and Gremlin
- Implement entity resolution, data enrichment, and graph-based ETL pipelines
- Apply graph reasoning, inference, and logic to build explainable AI systems
- Leverage knowledge graphs in real-world AI solutions—from chatbots and digital twins to recommendation systems, fraud detection, and multimodal reasoning
- Choose the right graph database technology for your use case (Neo4j, Amazon Neptune, ArangoDB, etc.)
- Integrate knowledge graphs with machine learning models using graph embeddings and hybrid AI techniques
This book doesn’t just teach you what knowledge graphs are—it shows you how to make them work in production environments, across sectors, at scale.
Whether you're architecting intelligent search, powering enterprise knowledge hubs, or enabling human-like reasoning in machines, Knowledge Graph Mastery is your blueprint for designing AI that knows what it’s doing.
Don’t just build AI that reacts—build AI that understands.Master knowledge graphs. Design smarter systems.
Start now.
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Paperback. Condition: new. Paperback. Artificial intelligence is evolving-and so should the way we build it.In a world driven by data, intelligence comes not just from the volume of information, but from the connections we can make between concepts. Knowledge graphs are at the forefront of this evolution, powering smarter AI systems that understand, reason, and adapt. From enterprise search to recommendation engines, from fraud detection to AI assistants, knowledge graphs enable machines to move from pattern recognition to true contextual understanding.Knowledge Graph Mastery is the definitive guide for building intelligent, scalable AI systems grounded in structured, semantic knowledge. Whether you're a software developer, AI engineer, data scientist, architect, or researcher, this book equips you with the tools, concepts, and real-world examples you need to master the design and deployment of modern knowledge-driven applications.This comprehensive, practical book takes you from foundational principles to advanced graph reasoning techniques. You'll explore how to structure and interlink information, model domain-specific ontologies, query complex graphs efficiently, and integrate them with machine learning workflows.Inside, you'll learn how to: Understand graph theory and graph thinking as a foundation for AIDesign semantic models using RDF, OWL, SHACL, and linked data principlesBuild and query scalable knowledge graphs using SPARQL, Cypher, and GremlinImplement entity resolution, data enrichment, and graph-based ETL pipelinesApply graph reasoning, inference, and logic to build explainable AI systemsLeverage knowledge graphs in real-world AI solutions-from chatbots and digital twins to recommendation systems, fraud detection, and multimodal reasoningChoose the right graph database technology for your use case (Neo4j, Amazon Neptune, ArangoDB, etc.)Integrate knowledge graphs with machine learning models using graph embeddings and hybrid AI techniquesThis book doesn't just teach you what knowledge graphs are-it shows you how to make them work in production environments, across sectors, at scale.Whether you're architecting intelligent search, powering enterprise knowledge hubs, or enabling human-like reasoning in machines, Knowledge Graph Mastery is your blueprint for designing AI that knows what it's doing.Don't just build AI that reacts-build AI that understands.Master knowledge graphs. Design smarter systems.Start now. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798315361312
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Knowledge Graph Mastery (Paperback)
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Paperback. Condition: new. Paperback. Artificial intelligence is evolving-and so should the way we build it.In a world driven by data, intelligence comes not just from the volume of information, but from the connections we can make between concepts. Knowledge graphs are at the forefront of this evolution, powering smarter AI systems that understand, reason, and adapt. From enterprise search to recommendation engines, from fraud detection to AI assistants, knowledge graphs enable machines to move from pattern recognition to true contextual understanding.Knowledge Graph Mastery is the definitive guide for building intelligent, scalable AI systems grounded in structured, semantic knowledge. Whether you're a software developer, AI engineer, data scientist, architect, or researcher, this book equips you with the tools, concepts, and real-world examples you need to master the design and deployment of modern knowledge-driven applications.This comprehensive, practical book takes you from foundational principles to advanced graph reasoning techniques. You'll explore how to structure and interlink information, model domain-specific ontologies, query complex graphs efficiently, and integrate them with machine learning workflows.Inside, you'll learn how to: Understand graph theory and graph thinking as a foundation for AIDesign semantic models using RDF, OWL, SHACL, and linked data principlesBuild and query scalable knowledge graphs using SPARQL, Cypher, and GremlinImplement entity resolution, data enrichment, and graph-based ETL pipelinesApply graph reasoning, inference, and logic to build explainable AI systemsLeverage knowledge graphs in real-world AI solutions-from chatbots and digital twins to recommendation systems, fraud detection, and multimodal reasoningChoose the right graph database technology for your use case (Neo4j, Amazon Neptune, ArangoDB, etc.)Integrate knowledge graphs with machine learning models using graph embeddings and hybrid AI techniquesThis book doesn't just teach you what knowledge graphs are-it shows you how to make them work in production environments, across sectors, at scale.Whether you're architecting intelligent search, powering enterprise knowledge hubs, or enabling human-like reasoning in machines, Knowledge Graph Mastery is your blueprint for designing AI that knows what it's doing.Don't just build AI that reacts-build AI that understands.Master knowledge graphs. Design smarter systems.Start now. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798315361312
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