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LLM Prompt Engineering for Developers
LLM Prompt Engineering for Developers

LLM Prompt Engineering for Developers: The Art and Science of Unlocking LLMs' True Potential

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Profile Icon Aymen El Amri
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Mex$410.99
eBook May 2024 251 pages 1st Edition
eBook
Mex$410.99
Arrow left icon
Profile Icon Aymen El Amri
Arrow right icon
Mex$410.99
eBook May 2024 251 pages 1st Edition
eBook
Mex$410.99
eBook
Mex$410.99

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Key benefits

  • In-depth coverage of prompt engineering from basics to advanced techniques.
  • Insights into cutting-edge methods like AutoCoT and transfer learning.
  • Comprehensive resource sections including prompt databases and tools.

Description

"LLM Prompt Engineering For Developers" begins by laying the groundwork with essential principles of natural language processing (NLP), setting the stage for more complex topics. It methodically guides readers through the initial steps of understanding how large language models work, providing a solid foundation that prepares them for the more intricate aspects of prompt engineering. As you proceed, the book transitions into advanced strategies and techniques that reveal how to effectively interact with and utilize these powerful models. From crafting precise prompts that enhance model responses to exploring innovative methods like few-shot and zero-shot learning, this resource is designed to unlock the full potential of language model technology. This book not only teaches the technical skills needed to excel in the field but also addresses the broader implications of AI technology. It encourages thoughtful consideration of ethical issues and the impact of AI on society. By the end of this book, readers will master the technical aspects of prompt engineering & appreciate the importance of responsible AI development, making them well-rounded professionals ready to focus on the advancement of this cutting-edge technology.

Who is this book for?

The target audience for "LLM Prompt Engineering For Developers" includes software developers, AI enthusiasts, technical team leads, advanced computer science students, and AI researchers with a basic understanding of artificial intelligence. Ideal for those looking to deepen their expertise in large language models and prompt engineering, this book serves as a practical guide for integrating advanced AI-driven projects and research into various workflows, assuming some foundational programming knowledge and familiarity with AI concepts.

What you will learn

  • Understand the principles of NLP and their application in LLMs.
  • Set up and configure environments for developing with LLMs.
  • Implement few-shot and zero-shot learning techniques.
  • Enhance LLM outputs through AutoCoT and self-consistency methods.
  • Apply transfer learning to adapt LLMs to new domains.
  • Develop practical skills in testing & scoring prompt effectiveness.

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : May 23, 2024
Length: 251 pages
Edition : 1st
Language : English
ISBN-13 : 9781836201724
Category :
Languages :

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon DRM FREE - Read whenever, wherever and however you want
OR
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Payment Processing...
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Product Details

Publication date : May 23, 2024
Length: 251 pages
Edition : 1st
Language : English
ISBN-13 : 9781836201724
Category :
Languages :

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Table of Contents

22 Chapters
From NLP to Large Language Models Chevron down icon Chevron up icon
Introduction to Prompt Engineering Chevron down icon Chevron up icon
OpenAI GPT and Prompting: An Introduction Chevron down icon Chevron up icon
Setting Up the Environment Chevron down icon Chevron up icon
Few-Shot Learning and Chain of Thought Chevron down icon Chevron up icon
Chain of Thought (CoT) Chevron down icon Chevron up icon
Zero-Shot CoT Prompting Chevron down icon Chevron up icon
Auto Chain of Thought Prompting (AutoCoT) Chevron down icon Chevron up icon
Self-Consistency Chevron down icon Chevron up icon
Transfer Learning Chevron down icon Chevron up icon
Perplexity as a Metric for Prompt Optimization Chevron down icon Chevron up icon
ReAct: Reason + Act Chevron down icon Chevron up icon
General Knowledge Prompting Chevron down icon Chevron up icon
Introduction to Azure Prompt Flow Chevron down icon Chevron up icon
LangChain: The Prompt Engineer’s Guide Chevron down icon Chevron up icon
A Practical Guide to Testing and Scoring Prompts Chevron down icon Chevron up icon
General Guidelines and Best Practices Chevron down icon Chevron up icon
How and Where Prompt Engineering Is Used Chevron down icon Chevron up icon
Anatomy of a Prompt Chevron down icon Chevron up icon
Types of Prompts Chevron down icon Chevron up icon
Prompt Databases, Tools, and Resources Chevron down icon Chevron up icon
Afterword Chevron down icon Chevron up icon
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