Mastering Large Language Models: Architectures, Applications, and Real-World Deployments of Large Language Models - Couverture souple
Synopsis
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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l'auteur
Ajay Rawat is a Data Engineer at the Hartree Centre, STFC, UKRI, with over 20 years of experience spanning academia, industry, and professional training. His expertise includes data engineering, cloud computing, AI/LLMs, and big data technologies. A former Assistant Professor, Ajay has delivered 200+ global trainings for organizations like Google, Citibank, and Walmart, and authored research in cloud computing, fault tolerance, and AI-driven systems. He holds a Ph.D. in Computer Science and Engineering and multiple certifications across Databricks, Google Cloud, and Confluent. He is based in London, UK.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Mastering Large Language Models: Architectures, Applications, and Real-World Deployments of Large Language Models
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Mastering Large Language Models (Paperback)
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Paperback. Etat : new. Paperback. 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9798868827327
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Mastering Large Language Models
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Mastering Large Language Models (Paperback)
impression à la demandeVendeur : CitiRetail, Stevenage, Royaume-Uni
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Paperback. Etat : new. Paperback. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798868827327
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Mastering Large Language Models : Architectures, Applications, and Real-World Deployments of Large Language Models
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Taschenbuch. Etat : 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. N° de réf. du vendeur 9798868827327
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