Engineering Large Language Models A Practical Guide From Design To Deployment
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Engineering Large Language Models: A Practical Guide from Design to Deployment
Discover the world of large language models with this comprehensive guide, designed to take you from the initial design stages to the final deployment. This book provides a practical approach to understanding the complexities and intricacies involved in engineering these powerful AI systems. Whether you are a seasoned professional or a curious beginner, this guide offers valuable insights and hands-on knowledge to help you navigate the challenges and opportunities in this cutting-edge field. The book begins by exploring the foundational concepts and principles that underpin large language models. You will learn about the different architectures, algorithms, and techniques used to create these models, as well as the various tools and frameworks available to support your work. Each chapter builds on the previous one, providing a structured and cohesive learning experience that ensures you gain a deep understanding of the subject matter. As you progress through the book, you will encounter real-world examples and case studies that illustrate the practical applications of large language models. These examples cover a wide range of industries and use cases, from natural language processing and sentiment analysis to machine translation and text generation.
A Practical Guide to Generative AI Using Amazon Bedrock
Author: Avik Bhattacharjee
language: en
Publisher: Springer Nature
Release Date: 2025-07-08
This comprehensive guide gives you the knowledge and skills you need to excel in Generative AI. From understanding the fundamentals to mastering techniques, this book offers a step-by-step approach to leverage Amazon Bedrock to build, deploy, and secure Generative AI applications. The book presents structured chapters and practical examples to delve into key concepts such as prompt engineering, retrieval-augmented generation, and model evaluation. You will gain profound insights into the Amazon Bedrock platform. The book covers setup, life cycle management, and integration with Amazon SageMaker. The book emphasizes real-world applications, and provides use cases and best practices across industries on topics such as text summarization, image generation, and conversational AI bots. The book tackles vital topics including data privacy, security, responsible AI practices, and guidance on navigating governance and monitoring challenges while ensuring adherence to ethical standards and regulations. The book provides the tools and knowledge needed to excel in the rapidly evolving field of Generative AI. Whether you're a data scientist, AI engineer, or business professional, this book will empower you to harness the full potential of Generative AI and drive innovation in your organization. What You Will Learn Understand the fundamentals of Generative AI and Amazon Bedrock Build Responsible Generative AI applications leveraging Amazon Bedrock Know techniques and best practices See real-world applications Integrate and manage platforms Handle securty and governance issues Evaluate and optimze models Gain future-ready insights Understand the project life cycle when building Generative AI Applications Who This Book Is For Data scientistys, AI/ML engineers and architects, software developers plus AI enthusiasts and studenta and educators, and leaders who want to evangelize within organizatios
Applied GPT-4 Systems
"Applied GPT-4 Systems" "Applied GPT-4 Systems" offers a comprehensive, expert-level exploration of building, deploying, and optimizing state-of-the-art generative AI using the transformative capabilities of GPT-4. It begins with a detailed breakdown of the model’s architecture, tracing the evolution of transformer models to the innovations and emergent behaviors unique to large language models at scale. Insights into parameter efficiency, advanced training techniques, and management of extensive context windows underscore the technical rigor and depth of coverage, ensuring readers develop a robust understanding of the foundation of GPT-4 systems. The book systematically advances through the essential elements of training and customizing GPT-4, delving into massive data acquisition, efficient distributed training, and the complex pipelines that enable real-world, mission-critical deployments. Readers will learn advanced strategies for model finetuning, domain specialization, and continual learning, while also mastering the intricacies of scalable infrastructure, performance optimization, and cost management required for enterprise-grade AI solutions. Each chapter is buttressed by real-world best practices for security, privacy, compliance, and robust model evaluation, equipping practitioners to build systems that are not only powerful, but also trustworthy and reliable. Finally, "Applied GPT-4 Systems" explores the cutting edge of AI application, from orchestrating conversational agents and multi-modal systems to embedding generative models in highly personalized, context-aware workflows and autonomous digital agents. With a forward-looking perspective on scaling, federated learning, explainable AI, and emerging research frontiers, this volume serves as both a technical reference and a strategic roadmap for professionals, researchers, and architects shaping the next generation of applied artificial intelligence with GPT-4.