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Building AI Agents with LLMs, RAG, and Knowledge Graphs: A practical guide to autonomous and modern AI agents
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À propos de cet article :
Marque : GENERIC
Vendu par KECHBOOK
Master LLM fundamentals to advanced techniques like RAG, reinforcement learning, and knowledge graphs to build, deploy, and scale intelligent AI agents that reason, retrieve, and act autonomouslyDRM-free PDF version + access to Packt's next-gen ReaderKey FeaturesImplement RAG and knowledge graphs for advanced problem-solvingLeverage innovative appr...
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Description produit
- Marque
- GENERIC
- Titre
- Building AI Agents with LLMs, RAG, and Knowledge Graphs: A practical guide to autonomous and modern AI agents
- Éditeur
- Packt Publishing
- Type de produit
- paperback
- Présentation du livre
- paperback
- Date de sortie
- 7/11/2025 12:00:00 AM
- Langue d'origine
- English
- ISBN
- 3640555244
- Dimensions
- 7.5 x 1.27 x 9.25 inches
- Nombre de pages
- 560 pages
- Langue
- English
- Résumé
- Master LLM fundamentals to advanced techniques like RAG, reinforcement learning, and knowledge graphs to build, deploy, and scale intelligent AI agents that reason, retrieve, and act autonomouslyDRM-free PDF version + access to Packt's next-gen ReaderKey FeaturesImplement RAG and knowledge graphs for advanced problem-solvingLeverage innovative approaches like LangChain to create real-world intelligent systemsIntegrate large language models, graph databases, and tool use for next-gen AI solutionsBook DescriptionThis book addresses the challenge of building AI that not only generates text but also grounds its responses in real data and takes action. Authored by AI specialists with expertise in drug discovery and systems optimization, this guide empowers you to leverage retrieval-augmented generation (RAG), knowledge graphs, and agent-based architectures to engineer truly intelligent behavior. By combining large language models (LLMs) with up-to-date information retrieval and structured knowledge, you'll create AI agents capable of deeper reasoning and more reliable problem-solving.Inside, you'll find a practical roadmap from concept to implementation. You’ll discover how to connect language models with external data via RAG pipelines for increasing factual accuracy and incorporate knowledge graphs for context-rich reasoning. The chapters will help you build and orchestrate autonomous agents that combine planning, tool use, and knowledge retrieval to achieve complex goals. Concrete Python examples and real-world case studies reinforce each concept and show how the techniques fit together.By the end of this book, you’ll be able to build intelligent AI agents that reason, retrieve, and interact dynamically, empowering you to deploy powerful AI solutions across industries.Email sign-up and proof of purchase requiredWhat you will learnLearn how LLMs work, their structure, uses, and limits, and design RAG pipelines to link them to external dataBuild and query knowledge grap
- Auteur
- Salvatore Raieli, Gabriele Iuculano
- Date de parution
- 7/11/2025 12:00:00 AM









