Preface

Large language models (LLMs) stand as a pivotal advancement in AI, enhancing everything from chatbots to complex decision systems. As LLM applications grow, so does the need for specialized operational strategies, which we explore through the lens of large language model operations (LLMOps). This book aims to bridge the gap between traditional machine learning operations (MLOps) and the specialized requirements of LLMOps, focusing on the development, deployment, and management of these models.

Essential Guide to LLMOps introduces practices tailored to the unique challenges of language models, addressing technological implementations and stringent security and compliance standards. Through each chapter, this book covers the life cycle of LLMs across various industries, providing insights into data collection, model development, monitoring, compliance, and future directions. It is designed for a broad audience, from data scientists and AI researchers to business leaders, offering a comprehensive guide on navigating and leading in the complex landscape of large-scale language model applications.