Mastering Prompt Engineering: Deep Insights for Optimizing Large Language Models (LLMs) is a comprehensive guide that takes readers on a journey through the world of Large Language Models (LLMs) and prompt engineering. Covering foundational concepts, advanced techniques, ethical considerations, and real-world case studies, this book equips both novices and experts to navigate the complex LLM landscape. It provides insights into LLM architecture, training, and prompt engineering methods, while addressing ethical concerns such as bias and privacy. Real-world case studies showcase the practical application of prompt engineering in a wide range of settings. This resource is not just for specialists but is a practical and ethically conscious guide for AI practitioners, students, scientific researchers, and anyone interested in harnessing the potential of LLMs in natural language processing and generation. Mastering Prompt Engineering serves as a gateway to a deeper understanding of LLMs and their responsible and effective utilization through its comprehensive, ethical, and practical approach.
1. Cover image - p. c 2. Title page - p. iii 3. Copyright - p. iv 4. Contents - p. v 5. About the Authors - p. xvii 6. Preface - p. xxi 7. Chapter 1 Basic insights into large language models (LLMs) - p. 1 8. Chapter 2 Foundations of prompt engineering - p. 25 9. Chapter 3 Familiarity with effective prompt design and process - p. 53 10. Chapter 4 Preprocessing and tokenization in prompt engineering - p. 73 11. Chapter 5 State-of-the-art techniques in prompt engineering - p. 101 12. Chapter 6 Various large language model types - p. 127 13. Chapter 7 Tools and platforms for prompt engineering - p. 161 14. Chapter 8 Evaluation and refinement of prompt engineering - p. 211 15. Chapter 9 Prompt engineering: Ethical considerations and challenges - p. 241 16. Chapter 10 Case studies in prompt engineering - p. 265 17. Chapter 11 Future trends in large language models and prompt engineering - p. 309 18. Index - p. 337
Mastering Prompt Engineering: Deep Insights for Optimizing Large Language Models (LLMs) is a comprehensive guide that takes readers on a journey through the world of Large Language Models (LLMs) and prompt engineering. Covering foundational concepts, advanced techniques, ethical considerations, and real-world case studies, this book equips both novices and experts to navigate the complex LLM landscape. It provides insights into LLM architecture, training, and prompt engineering methods, while addressing ethical concerns such as bias and privacy. Real-world case studies showcase the practical application of prompt engineering in a wide range of settings. This resource is not just for specialists but is a practical and ethically conscious guide for AI practitioners, students, scientific researchers, and anyone interested in harnessing the potential of LLMs in natural language processing and generation. Mastering Prompt Engineering serves as a gateway to a deeper understanding of LLMs and their responsible and effective utilization through its comprehensive, ethical, and practical approach.
1. Cover image - p. c 2. Title page - p. iii 3. Copyright - p. iv 4. Contents - p. v 5. About the Authors - p. xvii 6. Preface - p. xxi 7. Chapter 1 Basic insights into large language models (LLMs) - p. 1 8. Chapter 2 Foundations of prompt engineering - p. 25 9. Chapter 3 Familiarity with effective prompt design and process - p. 53 10. Chapter 4 Preprocessing and tokenization in prompt engineering - p. 73 11. Chapter 5 State-of-the-art techniques in prompt engineering - p. 101 12. Chapter 6 Various large language model types - p. 127 13. Chapter 7 Tools and platforms for prompt engineering - p. 161 14. Chapter 8 Evaluation and refinement of prompt engineering - p. 211 15. Chapter 9 Prompt engineering: Ethical considerations and challenges - p. 241 16. Chapter 10 Case studies in prompt engineering - p. 265 17. Chapter 11 Future trends in large language models and prompt engineering - p. 309 18. Index - p. 337
