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Bücher Englische Bücher Wissen & Bildung Naturwissenschaft, Medizin, Informatik, Technik Informatik & EDV Informatik Large Language Model Agents
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Large Language Model Agents
Muning Wen, Jianghao Lin, Weinan Zhang, Yong Yu (Gebundene Ausgabe, Englisch)
Optischer Zustand
Beschreibung
What if you could learn large‑model agents not by theory alone, but by building real, working systems from day one? This book offers exactly that: a practice‑driven, code‑grounded pathway into the rapidly evolving world of intelligent agents powered by large language models (LLM agents). Designed for AI researchers, practitioners, and postgraduate students, the book reveals why large‑model agents… matter now—and how their architectures, memory mechanisms, retrieval‑augmented generation (RAG), tool‑use strategies, and reasoning enhancements come together to form deployable intelligent systems. Rather than repeating definitions, it highlights the real challenges professionals face: How do you design an agent workflow that remains robust under noisy inputs? How do you debug a failing reasoning chain? How can an agent migrate smoothly across models or platforms? Rather than prescribing a single “best” solution, the book deliberately preserves open design questions and comparative experiments, encouraging readers to develop their own engineering judgment. Across four parts—agent foundations, agent architecture, agent fine‑tuning, and frontier topics such as multimodal agents, multi‑agent systems, agent safety, and agent protocols—this book blends conceptual clarity with executable Python examples and reproducible notebooks. Readers will learn prompt engineering techniques, memory and retrieval strategies, instruction tuning, LoRA and quantization workflows, reinforcement fine‑tuning , and practical evaluation and debugging methods. With only basic Python knowledge, readers can follow the “examples first, principles underneath” approach to master the essential skills for building, evaluating, and optimizing LLM agents. By the end, they will possess a complete methodological toolkit for stepping confidently into cutting‑edge agent research and real‑world applications. Dieses Produkt haben wir gerade leider nicht auf Lager.
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Technische Daten
Erscheinungsdatum
11.01.2027
Sprache
Englisch
EAN
9789819258291
Herausgeber
Springer Singapore
Serien- oder Bandtitel
Machine Learning: Foundations, Methodologies, and Applications
Sonderedition
Nein
Autor
Muning Wen, Jianghao Lin, Weinan Zhang, Yong Yu
Einbandart
Gebundene Ausgabe
Buch Untertitel
Design, Architecture, and Practical Implementation
Schlagwörter
Agent, Large Language Models (LLMs), Prompt Engineering, Agent Fine-Tuning, Retrieval-Augmented Generation, Multimodal, Agent Safety
Thema-Inhalt
UYQ - Künstliche Intelligenz
UYQM - Maschinelles Lernen
Höhe
235 mm
Breite
15.5 cm
Transparenz & Sicherheit
Hersteller: Springer Nature Customer Service Center GmbH, Europaplatz 3, Heidelberg, Deutschland, 69115, ProductSafety@springernature.com
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