LLM Prompt Engineering for Developers
The Art and Science of Unlocking LLMs' True Potential
1st Edition
Published on 23. September 2024
251 pages
978-1-83620-172-4 (ISBN)
Description
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Person
El Amri Aymen :
Aymen El Amri is a polymath software engineer, entrepreneur, and author with extensive experience in various technology fields, including DevOps & Cloud Native, Cloud Architecture, Python, NLP, and more. Aymen has authored multiple books and courses and provided training that has benefited thousands of developers and software engineers. His passion for teaching is evident in his practical approach, which simplifies complex concepts into understandable language and offers real-world examples that resonate with his audience. Aymen is the founder of several projects, including eralabs, FAUN, and MarketToDev, and he has been featured in several reputable publications.
Aymen El Amri is a polymath software engineer, entrepreneur, and author with extensive experience in various technology fields, including DevOps & Cloud Native, Cloud Architecture, Python, NLP, and more. Aymen has authored multiple books and courses and provided training that has benefited thousands of developers and software engineers. His passion for teaching is evident in his practical approach, which simplifies complex concepts into understandable language and offers real-world examples that resonate with his audience. Aymen is the founder of several projects, including eralabs, FAUN, and MarketToDev, and he has been featured in several reputable publications.
Content
Table of Contents - Preface
- From NLP to Large Language Models
- Introduction to Prompt Engineering
- OpenAI GPT and Prompting: An Introduction
- Setting Up the Environment
- Few-Shot Learning and Chain of Thought
- Chain of Thought (CoT)
- Zero-Shot CoT Prompting
- Auto Chain of Thought Prompting (AutoCoT)
- Self-Consistency
- Transfer Learning
- Perplexity as a Metric for Prompt Optimization
- ReAct: Reason + Act
- General Knowledge Prompting
- Introduction to Azure Prompt Flow
- LangChain: The Prompt Engineer's Guide
- A Practical Guide to Testing and Scoring Prompts
- General Guidelines and Best Practices
- How and Where Prompt Engineering Is Used
- Anatomy of a Prompt
- Types of Prompts
- Prompt Databases, Tools, and Resources
- Afterword
- From NLP to Large Language Models
- Introduction to Prompt Engineering
- OpenAI GPT and Prompting: An Introduction
- Setting Up the Environment
- Few-Shot Learning and Chain of Thought
- Chain of Thought (CoT)
- Zero-Shot CoT Prompting
- Auto Chain of Thought Prompting (AutoCoT)
- Self-Consistency
- Transfer Learning
- Perplexity as a Metric for Prompt Optimization
- ReAct: Reason + Act
- General Knowledge Prompting
- Introduction to Azure Prompt Flow
- LangChain: The Prompt Engineer's Guide
- A Practical Guide to Testing and Scoring Prompts
- General Guidelines and Best Practices
- How and Where Prompt Engineering Is Used
- Anatomy of a Prompt
- Types of Prompts
- Prompt Databases, Tools, and Resources
- Afterword
