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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
This book aims to bridge this gap by providing a comprehensive overview of prompt engineering. It covers the fundamental concepts of prompt engineering and offers practical guidelines and examples for creating effective prompts. The book also discusses different approaches to prompt engineerings, such as template-based, natural language, and mixed-initiative prompts.
In addition, this book provides an in-depth analysis of various evaluation metrics used to assess the effectiveness of prompts. It also covers the latest research trends and future directions in prompt engineering.
This book is intended for researchers, practitioners, and students interested in NLP and prompt engineering. It assumes some familiarity with NLP and machine learning concepts but is accessible to readers from diverse backgrounds. I hope this book will serve as a valuable resource and contribute to advancing the field of prompt engineering.
Author
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
This book aims to bridge this gap by providing a comprehensive overview of prompt engineering. It covers the fundamental concepts of prompt engineering and offers practical guidelines and examples for creating effective prompts. The book also discusses different approaches to prompt engineerings, such as template-based, natural language, and mixed-initiative prompts.
In addition, this book provides an in-depth analysis of various evaluation metrics used to assess the effectiveness of prompts. It also covers the latest research trends and future directions in prompt engineering.
This book is intended for researchers, practitioners, and students interested in NLP and prompt engineering. It assumes some familiarity with NLP and machine learning concepts but is accessible to readers from diverse backgrounds. I hope this book will serve as a valuable resource and contribute to advancing the field of prompt engineering.
Author