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Building AI Intensive Python Applications

You're reading from   Building AI Intensive Python Applications Create intelligent apps with LLMs and vector databases

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Product type Paperback
Published in Sep 2024
Publisher Packt
ISBN-13 9781836207252
Length 298 pages
Edition 1st Edition
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Table of Contents (18) Chapters Close

Preface 1. Chapter 1: Getting Started with Generative AI 2. Chapter 2: Building Blocks of Intelligent Applications FREE CHAPTER 3. Part 1: Foundations of AI: LLMs, Embedding Models, Vector Databases, and Application Design
4. Chapter 3: Large Language Models 5. Chapter 4: Embedding Models 6. Chapter 5: Vector Databases 7. Chapter 6: AI/ML Application Design 8. Part 2: Building Your Python Application: Frameworks, Libraries, APIs, and Vector Search
9. Chapter 7: Useful Frameworks, Libraries, and APIs 10. Chapter 8: Implementing Vector Search in AI Applications 11. Part 3: Optimizing AI Applications: Scaling, Fine-Tuning, Troubleshooting, Monitoring, and Analytics
12. Chapter 9: LLM Output Evaluation 13. Chapter 10: Refining the Semantic Data Model to Improve Accuracy 14. Chapter 11: Common Failures of Generative AI 15. Chapter 12: Correcting and Optimizing Your Generative AI Application 16. Other Books You May Enjoy Appendix: Further Reading: Index

Correcting and Optimizing Your Generative AI Application

Until this point, you’ve read about how to build a generative AI (GenAI) application, its various components, and how they fit together. You've gained a solid understanding of what makes them work (and not work) well. You’re also aware of some of the challenges of GenAI applications and how to identify them.

In this chapter, you’ll begin unraveling the mystery of how to improve your GenAI application once you’ve identified its shortcomings. You will also learn about optimizing and fine-tuning your GenAI application, so it’s a reliable, effective, and stable machine working in your favor, instead of a rogue actor bringing chaos.

This chapter will discuss several well-known techniques to improve your GenAI application, so you can be confident in your finished product. Ideally, you will perform all of these techniques. The chapter will define each of these and explain how they can improve...

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