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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

Product type Paperback

Published in Sep 2024

Publisher Packt

ISBN-13 9781836207252

Length 298 pages

Edition 1st Edition

Languages

Python

Tools

MongoDB

Concepts

Artificial Intelligence

Table of Contents (18) Chapters

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

Why subscribe?

AI/ML frameworks

AI/ML frameworks are essential tools that streamline the development and deployment of ML models, providing pre-built algorithms, optimized performance, and scalable solutions. They enable developers to focus on refining their models and GenAI applications rather than getting bogged down by low-level implementations. Using frameworks ensures efficiency, adaptability, and the ability to harness cutting-edge AI advancements. Developers should be interested in these frameworks as they also reduce development time and enhance the potential for breakthroughs in GenAI.

MongoDB has integrations with many AI/ML frameworks that may be familiar to developers, such as LangChain, LlamaIndex, Haystack, Microsoft Semantic Kernel, DocArray, and Flowise.

In this section, you will learn about LangChain, one of the most popular GenAI frameworks. Although it is very popular, it is certainly not the only popular framework. If you are interested in other frameworks, you can check...

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