Engineering AI Systems: Architecture and Devops Essentials
暫譯: 工程 AI 系統：架構與 DevOps 基礎

Bass, Len, Lu, Qinghua, Weber, Ingo

Engineering AI Systems: Architecture and Devops Essentials
  • 出版商: Addison Wesley
  • 出版日期: 2025-02-11
  • 售價: $2,010
  • 貴賓價: 9.5 折 $1,910
  • 語言: 英文
  • 頁數: 320
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 0138261415
  • ISBN-13: 9780138261412
  • 相關分類: DevOps、人工智慧

    • 海外代購書籍(需單獨結帳)

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商品描述

Master the Engineering of AI Systems: The Essential Guide for Architects and Developers

In today's rapidly evolving world, integrating artificial intelligence (AI) into your systems is no longer optional. Engineering AI Systems: Architecture and DevOps Essentials is a comprehensive guide to mastering the complexities of AI systems engineering. This book combines robust software architecture with cutting-edge DevOps practices to deliver high-quality, reliable, and scalable AI solutions.

Experts Len Bass, Qinghua Lu, Ingo Weber, and Liming Zhu demystify the complexities of engineering AI systems, providing practical strategies and tools for seamlessly incorporating AI in your systems. You will gain a comprehensive understanding of the fundamentals of AI and software engineering and how to combine them to create powerful AI systems. Through real-world case studies, the authors illustrate practical applications and successful implementations of AI in small- to medium-sized enterprises across various industries, and offer actionable strategies for designing, building, and operating AI systems that deliver real business value.

  • Lifecycle management of AI models, from data preparation to deployment
  • Best practices in system architecture and DevOps for AI systems
  • System reliability, performance, and security in AI implementations
  • Privacy and fairness in AI systems to build trust and achieve compliance
  • Effective monitoring and observability for AI systems to maintain operational excellence
  • Future trends in AI engineering to stay ahead of the curve

Equip yourself with the tools and understanding to lead your organization's AI initiatives. Whether you are a technical lead, software engineer, or business strategist, this book provides the essential insights you need to successfully engineer AI systems.

Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

商品描述(中文翻譯)

掌握人工智慧系統的工程：架構師和開發者的必備指南

在當今快速演變的世界中，將人工智慧（AI）整合到您的系統中已不再是選擇。工程AI系統：架構與DevOps要素是一本全面的指南，旨在掌握AI系統工程的複雜性。本書結合了穩健的軟體架構與尖端的DevOps實踐，以提供高品質、可靠且可擴展的AI解決方案。

專家Len Bass、Qinghua Lu、Ingo Weber和Liming Zhu揭開了工程AI系統的複雜性，提供實用的策略和工具，以無縫地將AI整合到您的系統中。您將全面了解AI和軟體工程的基本原則，以及如何將它們結合以創建強大的AI系統。通過真實案例研究，作者展示了AI在各行各業中小型至中型企業的實際應用和成功實施，並提供可行的策略來設計、建造和運營能夠帶來實際商業價值的AI系統。


  • AI模型的生命周期管理，從數據準備到部署

  • AI系統的系統架構和DevOps最佳實踐

  • AI實施中的系統可靠性、性能和安全性

  • AI系統中的隱私和公平性，以建立信任並實現合規

  • AI系統的有效監控和可觀察性，以維持運營卓越

  • AI工程的未來趨勢，以保持領先地位

為自己配備工具和理解，以引領您組織的AI計劃。無論您是技術負責人、軟體工程師還是商業策略師，本書提供了成功工程AI系統所需的基本見解。

註冊您的書籍以便方便訪問下載、更新和/或修正，隨著它們的可用性而提供。詳情請參見書內。

作者簡介

Dr. Len Bass is a seasoned researcher with over 30 years in software architecture and more than a decade in DevOps. He has been teaching DevOps to graduate students for seven years and is the author of a bestselling book on software architecture, along with three books on DevOps. Dr. Qinghua Lu is a principal research scientist at CSIRO's Data61, leading the Software Engineering for AI and Responsible AI science teams. She is a coauthor of Responsible AI: Best Practices for Creating Trustworthy AI Systems (Addison-Wesley, 2024). Prof. Dr. Ingo Weber is a professor at the Technical University of Munich and Director of Digital Transformation and ICT Infrastructure at Fraunhofer-Gesellschaft. He has written numerous publications and textbooks, including DevOps: A Software Architect's Perspective and Architecture for Blockchain Applications. Dr. Liming Zhu is a research director at CSIRO's Data61 and is a conjoint professor at University of New South Wales. He contributes to various AI safety and standards committees and has written over 300 papers. He is coauthor of Responsible AI: Best Practices for Creating Trustworthy AI Systems.

作者簡介(中文翻譯)

Len Bass 博士 是一位經驗豐富的研究者，在軟體架構領域擁有超過 30 年的經驗，並在 DevOps 領域有超過十年的經歷。他已經教授 DevOps 給研究生七年，並且是一本暢銷書《軟體架構》的作者，以及三本關於 DevOps 的書籍的作者。Qinghua Lu 博士 是 CSIRO 的 Data61 的首席研究科學家，領導人工智慧與負責任人工智慧科學團隊的軟體工程部門。她是《負責任的人工智慧：創建可信賴的人工智慧系統最佳實踐》（Addison-Wesley, 2024）的共同作者。Ingo Weber 教授 是慕尼黑工業大學的教授，並擔任 Fraunhofer-Gesellschaft 數位轉型與資訊通信技術基礎設施的主任。他撰寫了許多出版物和教科書，包括《DevOps：軟體架構師的視角》和《區塊鏈應用的架構》。Liming Zhu 博士 是 CSIRO 的 Data61 的研究主任，並且是新南威爾士大學的兼任教授。他參與各種人工智慧安全和標準委員會，並撰寫了超過 300 篇論文。他是《負責任的人工智慧：創建可信賴的人工智慧系統最佳實踐》的共同作者。

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