Mastering Large Language Models Architectures, Applications, and ReaWorld Deployments of Large Language Models | 41.75 MB
Title: Mastering Large Language Models Architectures, Applications, and ReaWorld Deployments of Large Language Models
Author: Ajay Rawat, Vardan Pathak
Category: Nonfiction, Science & Nature, Mathematics, Statistics, Computers, Advanced Computing, Artificial Intelligence, Programming, Programming Languages
Language: English | 589 Pages | ISBN: 9798868827334
Description:
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:
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.
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