Khan, Arshad

Business Intelligence and Data Analysis in the Age of AI

Campesato, Oswald

Beginning Python 3 with Claude 3

Fortino, Andres

Case Studies in Excel, R, and ChatGPT

Data Analysis for Business Decisions

Zherlitsyn, Dmytro

Financial Data Analysis Using Python

A Prompt-based Exploration of LLMs

Large Language Models for Developers

Goralski, Walter

Understanding AI, IoT, 6G and The Infrastructure Revolution

Beginning Python 3 with Grok 2

Herman, Erik

Using Analytics and Case Studies

Data Science for Decision Makers

Erik, Herman L.

Theory, Applications and Ethics

AI Revealed

CAMPESATO, OSWALD

CSS3 and SVG with Meta AI

Optimizing Prompt Engineering for Generative AI

Frontmatter

Contents

Preface

Chapter 1: Introduction to Prompt Engineering

Chapter 2: Crafting Effective Prompts

Chapter 3: Prompts and Contextual Understanding

Chapter 4: Fine-Tuning Prompts for Specific Use Cases

Chapter 5: Monitoring and Evaluating Prompt Performance

Chapter 6: Advanced Prompt Engineering Techniques

Chapter 7: Hands-On Exercises and Case Studies

Chapter 8: Best Practices and Future Directions

Index

Companion Files.zip

HERMAN, ERIK

In the constantly changing field of artificial intelligence, effective communication and prompt engineering have become essential for developers, researchers, and tech enthusiasts to guide and improve AI. Optimizing Prompt Engineering for Generative AI provides in-depth insight into the techniques and skills needed to create prompts that enhance the performance and relevance of conversational AI systems.

In the constantly changing field of artificial intelligence, effective communication and prompt engineering have become essential for developers,...

Format

Optimizing Prompt Engineering for Generative AI

ERIK HERMAN

Leute lesen auch