ISBN: 9798868827327 - mastering large language models: architectures, applications, and real-world deployments of large language models (7 Ergebnisse)

Zustand: New.

Zustand: NEW.

Taschenbuch. Zustand: Neu. Neuware - This book is a hands-on guide designed to help readers understand, build, and deploy powerful AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic systems, and intelligent chatbots.Starting with the fundamentals LLM architecture, tokenization, APIs, and fine-tuning the book gradually builds toward complex, integrated systems. Readers will learn to implement RAG pipelines using vector databases like FAISS and Pinecone, develop autonomous AI agents that complete multi-step tasks, and create real-world chatbots that understand and adapt to user needs. The approach is project-driven: each chapter includes visual explanations, step-by-step code walkthroughs, and deployment-ready examples. From building a personal assistant that searches your notes to creating a scheduling agent, every project reinforces both technical skills and applied understanding. It emphasizes clarity, inclusivity, and real-world relevance helping readers move confidently from basic understanding to complex applications.Whether you're exploring Agentic AI or looking to build production-ready systems, this book gives you the tools to turn curiosity into capability and innovation into impact.What you will learn:Build intelligent chatbots and tools using LLMs like GPT, LLaMA, and Mistral with guided development steps.Combine LLMs with vector databases like FAISS and Pinecone to create accurate, context-aware AI systems.Design AI agents capable of planning and executing complex workflows for automation and decision-making.Apply prompt engineering, memory, and multimodal tools to build real-world AI apps for your project portfolio.Who this book is for:Machine Learning engineers, data scientists, and AI professionals interested in learning how to build real-world AI systems using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, and intelligent chatbots.…

Taschenbuch. Zustand: Neu. Mastering Large Language Models | Architectures, Applications, and Real-World Deployments of Large Language Models | Ajay Rawat (u. a.) | Taschenbuch | xxx | Englisch | 2026 | Apress | EAN 9798868827327 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Taschenbuch. Zustand: Neu. Neuware -This book is a hands-on guide designed to help readers understand, build, and deploy powerful AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic systems, and intelligent chatbots.Starting with the fundamentalsLLM architecture, tokenization, APIs, and fine-tuningthe book gradually builds toward complex, integrated systems. Readers will learn to implement RAG pipelines using vector databases like FAISS and Pinecone, develop autonomous AI agents that complete multi-step tasks, and create real-world chatbots that understand and adapt to user needs. The approach is project-driven: each chapter includes visual explanations, step-by-step code walkthroughs, and deployment-ready examples. From building a personal assistant that searches your notes to creating a scheduling agent, every project reinforces both technical skills and applied understanding. It emphasizes clarity, inclusivity, and real-world relevancehelping readers move confidently from basic understanding to complex applications.Whether you're exploring Agentic AI or looking to build production-ready systems, this book gives you the tools to turn curiosity into capabilityand innovation into impact.What you will learn:- Build intelligent chatbots and tools using LLMs like GPT, LLaMA, and Mistral with guided development steps.- Combine LLMs with vector databases like FAISS and Pinecone to create accurate, context-aware AI systems.- Design AI agents capable of planning and executing complex workflows for automation and decision-making.- Apply prompt engineering, memory, and multimodal tools to build real-world AI apps for your project portfolio.Who this book is for:Machine Learning engineers, data scientists, and AI professionals interested in learning how to build real-world AI systems using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, and intelligent chatbots.Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg 600 pp. Englisch.…

Zustand: New.

Taschenbuch. Zustand: Neu. Neuware -This book is a hands-on guide designed to help readers understand, build, and deploy powerful AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic systems, and intelligent chatbots.Starting with the fundamentalsLLM architecture, tokenization, APIs, and fine-tuningthe book gradually builds toward complex, integrated systems. Readers will learn to implement RAG pipelines using vector databases like FAISS and Pinecone, develop autonomous AI agents that complete multi-step tasks, and create real-world chatbots that understand and adapt to user needs. The approach is project-driven: each chapter includes visual explanations, step-by-step code walkthroughs, and deployment-ready examples. From building a personal assistant that searches your notes to creating a scheduling agent, every project reinforces both technical skills and applied understanding. It emphasizes clarity, inclusivity, and real-world relevancehelping readers move confidently from basic understanding to complex applications.Whether you're exploring Agentic AI or looking to build production-ready systems, this book gives you the tools to turn curiosity into capabilityand innovation into impact.What you will learn:Build intelligent chatbots and tools using LLMs like GPT, LLaMA, and Mistral with guided development steps.Combine LLMs with vector databases like FAISS and Pinecone to create accurate, context-aware AI systems.Design AI agents capable of planning and executing complex workflows for automation and decision-making.Apply prompt engineering, memory, and multimodal tools to build real-world AI apps for your project portfolio.Who this book is for:Machine Learning engineers, data scientists, and AI professionals interested in learning how to build real-world AI systems using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, and intelligent chatbots. 632 pp. Englisch.…