Machine Learning Engineering in Action
暫譯: 實作中的機器學習工程

Wilson, Ben

Machine Learning Engineering in Action
  • 出版商: Manning
  • 出版日期: 2022-04-26
  • 定價: $2,150
  • 售價: 8.8 折 $1,892 (限時優惠至 2025-03-31)
  • 語言: 英文
  • 頁數: 300
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1617298719
  • ISBN-13: 9781617298714
  • 相關分類: Machine Learning
  • 相關翻譯: 機器學習項目交付實戰 (簡中版)

    • 立即出貨 (庫存=1)

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商品描述

Field-tested tips, tricks, and design patterns for building Machine Learning projects that are deployable, maintainable, and secure from concept to production.

Machine Learning Engineering in Action lays out an approach to building deployable, maintainable production machine learning systems. You'll adopt software development standards that deliver better code management, and make it easier to test, scale, and even reuse your machine learning code!

You'll learn how to plan and scope your project, manage cross-team logistics that avoid fatal communication failures, and design your code's architecture for improved resilience. You'll even discover when not to use machine learning--and the alternative approaches that might be cheaper and more effective. When you're done working through this toolbox guide, you'll be able to reliably deliver cost-effective solutions for organizations big and small alike.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

商品描述(中文翻譯)

經過實地測試的技巧、竅門和設計模式，用於構建可部署、可維護且安全的機器學習專案，從概念到生產。

機器學習工程實務 提出了構建可部署、可維護的生產機器學習系統的方法。您將採用軟體開發標準，以提供更好的程式碼管理，並使測試、擴展甚至重用您的機器學習程式碼變得更加容易！

您將學習如何規劃和範圍您的專案，管理跨團隊的物流，以避免致命的溝通失誤，並設計您的程式碼架構以提高韌性。您甚至會發現何時不應使用機器學習，以及可能更便宜且更有效的替代方法。當您完成這本工具箱指南後，您將能夠為大小組織可靠地提供具成本效益的解決方案。

購買印刷書籍可獲得Manning Publications提供的免費電子書，格式包括PDF、Kindle和ePub。

作者簡介

Ben Wilson has worked as a professional data scientist for more than ten years. He currently works as a resident solutions architect at Databricks, where he focuses on machine learning production architecture with companies ranging from 5-person startups to global Fortune 100. Ben is the creator and lead developer of the Databricks Labs AutoML project, a Scala-and Python-based toolkit that simplifies machine learning feature engineering, model tuning, and pipeline-enabled modeling.

作者簡介(中文翻譯)

本·威爾森擔任專業數據科學家已有十多年。他目前在 Databricks 擔任常駐解決方案架構師，專注於機器學習生產架構，服務的公司範圍從五人初創企業到全球《財富》100 強企業。Ben 是 Databricks Labs AutoML 項目的創建者和首席開發者，這是一個基於 Scala 和 Python 的工具包，旨在簡化機器學習特徵工程、模型調整和管道驅動的建模。

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