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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 FREE CHAPTER 2. Chapter 2: Building Blocks of Intelligent Applications 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

Python for AI/ML

Python has established itself as the go-to programming language in various fields, but most notably in AI, ML, and building applications powered by large language models (LLMs). Python offers simplicity, readability, and a robust ecosystem of libraries, making it an ideal choice for all kinds of users, whether they are developers, researchers, or even students just getting started with programming. Python has also emerged as the language of choice for building new LLM-powered applications, underscoring Python’s usefulness, popularity, and versatility.

In this section, you will learn some of the reasons that make Python a great choice for building modern AI-powered applications:

  • Simplicity and readability: Python’s syntax is designed to be intuitive and clear, which is one of its core strengths. Python can represent complex algorithms and tasks in a few lines of code that are easily readable and understandable.
  • Rich ecosystem of libraries...
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