Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Unlocking the Secrets of Prompt Engineering

You're reading from   Unlocking the Secrets of Prompt Engineering Master the art of creative language generation to accelerate your journey from novice to pro

Arrow left icon
Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781835083833
Length 316 pages
Edition 1st Edition
Concepts
Arrow right icon
Author (1):
Arrow left icon
Gilbert Mizrahi Gilbert Mizrahi
Author Profile Icon Gilbert Mizrahi
Gilbert Mizrahi
Arrow right icon
View More author details
Toc

Table of Contents (18) Chapters Close

Preface 1. Part 1:Introduction to Prompt Engineering FREE CHAPTER
2. Chapter 1: Understanding Prompting and Prompt Techniques 3. Chapter 2: Generating Text with AI for Content Creation 4. Part 2:Basic Prompt Engineering Techniques
5. Chapter 3: Creating and Promoting a Podcast Using ChatGPT and Other Practical Examples 6. Chapter 4: LLMs for Creative Writing 7. Chapter 5: Unlocking Insights from Unstructured Text – AI Techniques for Text Analysis 8. Part 3: Advanced Use Cases for Different Industries
9. Chapter 6: Applications of LLMs in Education and Law 10. Chapter 7: The Rise of AI Pair Programmers – Teaming Up with Intelligent Assistants for Better Code 11. Chapter 8: AI for Chatbots 12. Chapter 9: Building Smarter Systems – Advanced LLM Integrations 13. Part 4:Ethics, Limitations, and Future Developments
14. Chapter 10: Generative AI – Emerging Issues at the Intersection of Ethics and Innovation 15. Chapter 11: Conclusion 16. Index 17. Other Books You May Enjoy

Sentiment analysis – AI techniques for emotion detection in text

Sentiment analysis is one of the key applications of AI techniques in the field of prompt engineering. As the first in a series of AI applications we will cover, sentiment analysis uses natural language processing to identify and extract emotional signals from text data. The goal is to gauge the overall attitude or feeling within a piece of writing, for instance, determining whether a product review is positive or negative.

The most common uses of sentiment analysis are as follows:

  • Brand monitoring: Brands can track conversations happening online to monitor their reputation. Sentiment analysis allows them to detect PR issues as they emerge and measure the impact of marketing campaigns.
  • Customer service: Customer experience teams can aggregate feedback at scale by analyzing surveys, reviews, and social media mentions. This provides data-driven insights into where people are satisfied or frustrated...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime