SKU/Artículo: AMZ-B0FH2P1WZ7
Graph-Based Context Systems: Design, Implementation, and Integration for Intelligent Applications
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Paperback
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Disponibilidad:
En stock
En stock
Peso con empaque:
0.22 kg
0.22 kg
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Sí
Sí
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Nuevo
Nuevo
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Amazon
Amazon
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USA
USA
Sobre este producto
- Graph-Based Context Systems: Design, Implementation, and Integration for Intelligent Applications Tired of LLMs providing confident but incorrect answers? Discover how graph-based context systems can ground your AI in truth, enhancing reasoning, and delivering context-aware insights. In this essential guide, Tony Larson equips you with the expertise to leverage graph-based context systems for transforming Large Language Models (LLMs). Learn to overcome LLM limitations like hallucinations and lack of explainability by creating powerful graphs that structure knowledge and relationships. Key Features of This Indispensable Resource:Solidify Graph Foundations: Master the core components of graphs—nodes, edges, and properties—and understand design patterns like star, snowflake, and hub-and-spoke for efficient data organization. Explore schema-less vs. schema-driven designs and scalability strategies for large-scale graphs.Practical Implementation: Build graphs using leading tools like Neo4j, TigerGraph, and FalkorDB. Learn techniques for data ingestion from structured and unstructured sources, graph construction with LLMs, and enrichment to ensure data quality.Seamless Integration with LLMs: Implement advanced techniques such as GraphRAG, hybrid approaches combining graphs and vector databases, and prompt engineering to make LLMs graph-aware. Address challenges like data leakage and ensure LLMs understand graph structures.Real-World Applications: Explore how graphs are transforming industries, with case studies in healthcare (mapping medical knowledge), finance (fraud detection), search engines (enhancing relevance), recommendation systems (personalized suggestions), and social networks (trend analysis).Future-Proof Your Skills: Stay ahead with insights into challenges like data quality, scalability, and real-time updates. Discover emerging trends such as AI-enhanced graph construction, graph-native LLMs, and hybrid systems that combine multiple data models.Why This Book Matters In an era where data is increasingly interconnected, graph-based context systems are essential for unlocking the full potential of AI. This book provides the knowledge and practical skills to build systems that are not only intelligent but also grounded in structured, relational data, ensuring reliability and context awareness. Who This Book Is For This book is perfect for data scientists, AI practitioners, and industry professionals eager to harness the power of graphs for intelligent applications. Whether you’re designing a knowledge graph for healthcare, integrating graphs with LLMs for customer service, or exploring graph-based solutions for finance, this guide equips you with the tools and insights to succeed. What You’ll Gain By the end of this book, you’ll have the knowledge and tools to design, implement, and integrate graph-based context systems that elevate your AI applications to new heights of intelligence, reliability, and context awareness. With clear explanations, practical examples, and a focus on real-world impact, Graph-Based Context Systems is your roadmap to building AI that is not only smart but also transparent and ready for enterprise deployment.
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AR$28.853
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AR$19.893
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