Building AI Intensive Python Applications
Building AI Intensive Python Applications
Create intelligent apps with LLMs and vector databases
About the Book
The era of generative AI is upon us, and this book serves as a roadmap to harness its full potential. With its help, you’ll learn the core components of the AI stack: large language models (LLMs), vector databases, and Python frameworks, and see how these technologies work together to create intelligent applications.
The chapters will help you discover best practices for data preparation, model selection, and fine-tuning, and teach you advanced techniques such as retrieval-augmented generation (RAG) to overcome common challenges, such as hallucinations and data leakage. You’ll get a solid understanding of vector databases, implement effective vector search strategies, refine models for accuracy, and optimize performance to achieve impactful results. You’ll also identify and address AI failures to ensure your applications deliver reliable and valuable results. By evaluating and improving the output of LLMs, you’ll be able to enhance their performance and relevance.
By the end of this book, you’ll be well-equipped to build sophisticated AI applications that deliver real-world value.
About the Author
Table of Contents
- Getting Started with Generative AI
- Building Blocks of Intelligent Applications
- Large Language Models
- Embedding Models
- Vector Databases
- AI/ML Application Design
- Useful Frameworks, Libraries, and APIs
- Implementing Vector Search in AI Applications
- LLM Output Evaluation
- Refining the Semantic Data Model to Improve Accuracy
- Common Failures of Generative AI
- Correcting and Optimizing Your Generative AI Application
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