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Building AI Intensive Python Applications
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Building AI Intensive Python Applications
By:
Overview of this 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.
Table of Contents (18 chapters)
Preface
Chapter 1: Getting Started with Generative AI
Chapter 2: Building Blocks of Intelligent Applications
Part 1: Foundations of AI: LLMs, Embedding Models, Vector Databases, and Application Design
Chapter 3: Large Language Models
Chapter 4: Embedding Models
Chapter 5: Vector Databases
Chapter 6: AI/ML Application Design
Part 2: Building Your Python Application: Frameworks, Libraries, APIs, and Vector Search
Chapter 7: Useful Frameworks, Libraries, and APIs
Chapter 8: Implementing Vector Search in AI Applications
Part 3: Optimizing AI Applications: Scaling, Fine-Tuning, Troubleshooting, Monitoring, and Analytics
Chapter 9: LLM Output Evaluation
Chapter 10: Refining the Semantic Data Model to Improve Accuracy
Chapter 11: Common Failures of Generative AI
Chapter 12: Correcting and Optimizing Your Generative AI Application
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Appendix: Further Reading: Index
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