This book dives into the intricacies of prompt engineering specifically for large language models (LLMs), equipping readers with the tools to build successful applications using LLMs. The authors, John Berryman and Albert Ziegler, cover the methodologies behind crafting prompts that optimize LLM outputs for real-world applications. Readers will explore key strategies, techniques, and best practices for integrating LLMs in a variety of use cases, from chatbots to content generation.

Why Read This Book

• In-Depth LLM Insights: Understand the inner workings of large language models and their potential in modern applications.
• Practical Guidance: Learn how to construct prompts that guide LLMs to produce accurate, relevant, and high-quality outputs.
• Real-World Applications: Discover how to apply these techniques in industries like customer service, healthcare, and education.
• Step-by-Step Approach: The book presents a step-by-step approach for engineering LLM prompts to achieve desired results with minimal errors.

About the Authors

John Berryman An expert in machine learning and natural language processing (NLP), John has worked on numerous projects applying LLMs to diverse sectors. His work focuses on improving the accuracy and efficiency of AI-driven models.Albert Ziegler A well-regarded researcher in AI and NLP, Albert's contributions to the development of language models have helped push the boundaries of AI applications in business, technology, and academia.