Applied Knowledge Graphs for LLMs: Designing, Implementing, and Integrating Graph-Based Context Systems (Explainable & Context-Aware AI Systems) - Softcover
Book 2 of 2: Explainable & Context-Aware AI Systems
Synopsis
Applied Knowledge Graphs for LLMs: Designing, Implementing, and Integrating Graph-Based Context Systems
Building on the foundational concepts of intelligent and explainable AI, this second volume in the Explainable & Context-Aware AI Systems series plunges into the practical implementation of Knowledge Graphs for Large Language Models.
Tired of LLMs providing confident but incorrect answers? Ground your AI in truth.
This essential resource equips AI practitioners, data architects, and developers with the expertise to leverage Applied Knowledge Graphs for transforming Large Language Models. Learn to overcome LLM limitations like hallucinations and lack of explainability by creating powerful graph-based context systems.
Key features of this indispensable guide:
Reinforce KG Foundations: Solidify your understanding of knowledge representation, schema design, and data modeling for Knowledge Graphs through practical application.
LLM-Powered KG Construction: Master practical methods for automated entity and relationship extraction from unstructured text using LLMs and prompt engineering.
Deep Integration Patterns: Implement Retrieval-Augmented Generation (RAG), multi-hop reasoning, and LLM-guided agents for superior performance.
Operational Excellence: Discover best practices for scalable architecture, performance optimization, security, and data governance in KG-LLM environments.
Evaluation & Improvement: Learn strategies for benchmarking KG quality and LLM performance, including human-in-the-loop processes and A/B testing.
With practical examples and a focus on real-world application, this book is your roadmap to building contextual AI solutions that are not only intelligent but also reliable, transparent, and ready for enterprise deployment.
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Paperback. Condition: new. Paperback. Applied Knowledge Graphs for LLMs: Designing, Implementing, and Integrating Graph-Based Context SystemsBuilding on the foundational concepts of intelligent and explainable AI, this second volume in the Explainable & Context-Aware AI Systems series plunges into the practical implementation of Knowledge Graphs for Large Language Models.Tired of LLMs providing confident but incorrect answers? Ground your AI in truth.This essential resource equips AI practitioners, data architects, and developers with the expertise to leverage Applied Knowledge Graphs for transforming Large Language Models. Learn to overcome LLM limitations like hallucinations and lack of explainability by creating powerful graph-based context systems.Key features of this indispensable guide: Reinforce KG Foundations: Solidify your understanding of knowledge representation, schema design, and data modeling for Knowledge Graphs through practical application.LLM-Powered KG Construction: Master practical methods for automated entity and relationship extraction from unstructured text using LLMs and prompt engineering.Deep Integration Patterns: Implement Retrieval-Augmented Generation (RAG), multi-hop reasoning, and LLM-guided agents for superior performance.Operational Excellence: Discover best practices for scalable architecture, performance optimization, security, and data governance in KG-LLM environments.Evaluation & Improvement: Learn strategies for benchmarking KG quality and LLM performance, including human-in-the-loop processes and A/B testing.With practical examples and a focus on real-world application, this book is your roadmap to building contextual AI solutions that are not only intelligent but also reliable, transparent, and ready for enterprise deployment. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798291352557
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Paperback. Condition: new. Paperback. Applied Knowledge Graphs for LLMs: Designing, Implementing, and Integrating Graph-Based Context SystemsBuilding on the foundational concepts of intelligent and explainable AI, this second volume in the Explainable & Context-Aware AI Systems series plunges into the practical implementation of Knowledge Graphs for Large Language Models.Tired of LLMs providing confident but incorrect answers? Ground your AI in truth.This essential resource equips AI practitioners, data architects, and developers with the expertise to leverage Applied Knowledge Graphs for transforming Large Language Models. Learn to overcome LLM limitations like hallucinations and lack of explainability by creating powerful graph-based context systems.Key features of this indispensable guide: Reinforce KG Foundations: Solidify your understanding of knowledge representation, schema design, and data modeling for Knowledge Graphs through practical application.LLM-Powered KG Construction: Master practical methods for automated entity and relationship extraction from unstructured text using LLMs and prompt engineering.Deep Integration Patterns: Implement Retrieval-Augmented Generation (RAG), multi-hop reasoning, and LLM-guided agents for superior performance.Operational Excellence: Discover best practices for scalable architecture, performance optimization, security, and data governance in KG-LLM environments.Evaluation & Improvement: Learn strategies for benchmarking KG quality and LLM performance, including human-in-the-loop processes and A/B testing.With practical examples and a focus on real-world application, this book is your roadmap to building contextual AI solutions that are not only intelligent but also reliable, transparent, and ready for enterprise deployment. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798291352557
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