商品描述
This book provides a comprehensive exploration of LangChain, empowering you to effectively harness large language models (LLMs) for Gen AI applications. It focuses on practical implementation and techniques, making it a valuable resource for learning LangChain. The book starts with foundational topics such as environment setup and building basic chains, then delves into key components such as prompt templates, tool integration, and memory management. You will also explore practical topics such as output parsing, embedding models, and developing chatbots and retrieval-augmented generation (RAG) systems. Additional chapters focus on integrating LangChain with other AI tools and deploying applications while emphasizing best practices for AI ethics and performance. By the time you finish this book, you'll have the know-how to confidently build Generative AI solutions using LangChain. Whether you're exploring practical applications or curious about the latest trends, this guide gives you the tools and insights to solve real-world AI problems. You'll be ready to design smart, data-driven applications--and rethink how you approach Generative AI.
What You Will Learn
Understand the core ideas, architecture, and essential features of the LangChain framework Create advanced LLM-driven workflows and applications that address real-world challenges - Develop robust Retrieval-Augmented Generation (RAG) systems using LangChain, vector databases, and proven best practices for retrieving and generating high-quality responses
Who This Book Is For
Data scientists and AI enthusiasts with basic Python skills who want to use LangChain for advanced development, and Python developers interested in building data-responsive applications with large language models (LLMs)
商品描述(中文翻譯)
本書全面探討 LangChain，幫助您有效利用大型語言模型（LLMs）來開發生成式人工智慧（Gen AI）應用程式。它專注於實際實作和技術，使其成為學習 LangChain 的寶貴資源。
本書從環境設置和建立基本鏈的基礎主題開始，然後深入探討關鍵組件，如提示模板、工具整合和記憶管理。您還將探索實用主題，如輸出解析、嵌入模型，以及開發聊天機器人和檢索增強生成（RAG）系統。額外的章節專注於將 LangChain 與其他 AI 工具整合及應用程式部署，同時強調 AI 倫理和性能的最佳實踐。
當您完成本書時，您將具備自信地使用 LangChain 建立生成式 AI 解決方案的能力。無論您是在探索實際應用還是對最新趨勢感到好奇，本指南都將為您提供解決現實世界 AI 問題的工具和見解。您將準備好設計智能、數據驅動的應用程式，並重新思考您對生成式 AI 的看法。
您將學到的內容
- 了解 LangChain 框架的核心理念、架構和基本特徵
- 創建針對現實挑戰的高級 LLM 驅動工作流程和應用程式
- 使用 LangChain、向量資料庫和經驗證的最佳實踐開發穩健的檢索增強生成（RAG）系統，以檢索和生成高品質的回應
本書適合誰
具備基本 Python 技能的數據科學家和 AI 愛好者，想要使用 LangChain 進行高級開發，以及對使用大型語言模型（LLMs）構建數據響應應用程式感興趣的 Python 開發者。
作者簡介
Sanath Raj B Narayan is a Senior Data Scientist with over a decade of experience in building AI and machine learning solutions, as well as scalable systems using AWS and Azure. He has previously held roles at Ericsson, Mindtree, KPMG India, and Cognizant, where he led data-driven projects across the retail, telecom, and consulting sectors. Sanathraj's expertise spans predictive modeling, recommender systems, and the deployment of end-to-end machine learning pipelines. He is also a regular speaker at conferences, where he presents on AI and related topics. Nitin Agarwal is a Principal AI Scientist with over 14 years of experience in Artificial Intelligence and Data Science. Formerly a Senior Data Scientist at Microsoft, he specializes in Machine Learning, Deep Learning, Natural Language Processing, and Statistical Modeling. Nitin brings extensive expertise in crafting innovative AI Copilots and delivering cutting-edge Data Science solutions across diverse industries, including Healthcare, Technology, and Logistics. He holds a master's degree in Data Science and Engineering from Birla Institute of Technology and Sciences (BITS), Pilani and CORe from Harvard Business School (HBX). Passionate about Generative AI and Large Language Models (LLMs), he is also a published researcher and a dedicated mentor. Nitin frequently shares his expertise as a speaker at AI and technology conferences, where he engages with the community on the latest advancements in AI and their real-world applications.
作者簡介(中文翻譯)
Sanath Raj B Narayan 是一位資深數據科學家，擁有超過十年的經驗，專注於構建人工智慧（AI）和機器學習解決方案，以及使用 AWS 和 Azure 建立可擴展系統。他曾在 Ericsson、Mindtree、KPMG 印度和 Cognizant 擔任職務，領導零售、電信和諮詢領域的數據驅動專案。Sanathraj 的專業領域包括預測建模、推薦系統以及端到端機器學習管道的部署。他也是會議的常規演講者，分享有關 AI 和相關主題的演講。
Nitin Agarwal 是一位首席 AI 科學家，擁有超過 14 年的人工智慧和數據科學經驗。曾任 Microsoft 的資深數據科學家，他專精於機器學習、深度學習、自然語言處理和統計建模。Nitin 在創造創新的 AI 副駕駛和提供尖端數據科學解決方案方面擁有豐富的專業知識，涵蓋醫療保健、科技和物流等多個行業。他擁有比爾拉科技與科學學院（BITS）皮拉尼校區的數據科學與工程碩士學位，以及哈佛商學院（HBX）的 CORe 課程。對生成式 AI 和大型語言模型（LLMs）充滿熱情的他，也是已發表的研究者和專注的導師。Nitin 經常作為演講者在 AI 和科技會議上分享他的專業知識，與社群互動，討論 AI 的最新進展及其在現實世界中的應用。
