构建人工智能密集型Python应用程序：使用LLM和向量数据库创建智能应用程序

English | 2024 | ISBN: 9781836207252 | 388 pages | True EPUB | 6.8 MB

Master retrieval-augmented generation architecture and fine-tune your AI stack, along with discovering real-world use cases and best practices to create powerful AI apps

Key Features Get to grips with the fundamentals of LLMs, vector databases, and Python frameworks Implement effective retrieval-augmented generation strategies with MongoDB Atlas Optimize AI models for performance and accuracy with model compression and deployment optimization

Book Description 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.

What you will learn Understand the architecture and components of the generative AI stack Explore the role of vector databases in enhancing AI applications Master Python frameworks for AI development Implement Vector Search in AI applications Find out how to effectively evaluate LLM output Overcome common failures and challenges in AI development

Who this book is for This book is for software engineers and developers looking to build intelligent applications using generative AI. While the book is suitable for beginners, a basic understanding of Python programming is required to make the most of it.

英文| 2024 |国际标准图书编号：9781836207252 | 388页|真正的EPUB | 6.8 MB 掌握检索增强生成架构，微调您的AI堆栈，同时发现真实世界的用例和最佳实践，以创建强大的AI应用程序 主要功能掌握LLM、向量数据库和Python框架的基础知识使用MongoDB Atlas实现有效的检索增强生成策略通过模型压缩和部署优化优化AI模型的性能和准确性 生成式人工智能的时代已经到来，这本书是利用其全部潜力的路线图。在它的帮助下，您将学习AI堆栈的核心组件：大型语言模型（LLM）、向量数据库和Python框架，并了解这些技术如何协同工作以创建智能应用程序。 本章将帮助您发现数据准备、模型选择和微调的最佳实践，并教您高级技术，如检索增强生成（RAG），以克服常见的挑战，如幻觉和数据泄露。您将深入了解向量数据库，实施有效的向量搜索策略，优化模型以提高准确性，并优化性能以获得有影响力的结果。您还将识别和解决人工智能故障，以确保您的应用程序提供可靠和有价值的结果。通过评估和改进LLM的输出，您将能够提高它们的性能和相关性。 到本书结束时，你将具备构建复杂的人工智能应用程序的能力，这些应用程序可以提供现实世界的价值。 你将学习什么了解生成式AI堆栈的架构和组件探索向量数据库在增强AI应用程序中的作用掌握AI开发的Python框架在人工智能应用程序中实现向量搜索找出如何有效评估LLM输出克服AI开发中的常见故障和挑战 这本书适合谁这本书是为希望使用生成式人工智能构建智能应用程序的软件工程师和开发人员编写的。虽然这本书适用于初学者，但需要对Python编程有基本的了解才能充分利用它。

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