The Definitive Guide to Machine Learning Operations in AWS: Machine Learning Scalability and Optimization with AWS

Sendas, Neel, Rajale, Deepali

The Definitive Guide to Machine Learning Operations in AWS: Machine Learning Scalability and Optimization with AWS
  • 出版商: Apress
  • 出版日期: 2024-12-31
  • 售價: $2,360
  • 貴賓價: 9.5 折 $2,242
  • 語言: 英文
  • 頁數: 390
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9798868810756
  • ISBN-13: 9798868810756
  • 相關分類: Amazon Web Services、JVM 語言、Machine Learning

    • 尚未上市，無法訂購

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商品描述

This book focuses on deploying, testing, monitoring, and automating ML systems in production. It covers AWS MLOPS tools like Amazon SageMaker, Data Wrangler, and AWS Feature Store, along with best practices for operating ML systems on AWS.

This book explains how to design, develop, and deploy ML workloads at scale using AWS cloud's well-architected pillars. It starts with an introduction to AWS services and MLOps tools, setting up the MLOps environment. It covers operational excellence, including CI/CD pipelines and Infrastructure as code. Security in MLOps, data privacy, IAM, and reliability with automated testing are discussed. Performance efficiency and cost optimization, like Right-sizing ML resources, are explored. The book concludes with MLOps best practices, MLOPS for GenAI, emerging trends, and future developments in MLOps

By the end, readers will learn operating ML workloads on the AWS cloud. This book suits software developers, ML engineers, DevOps engineers, architects, and team leaders aspiring to be MLOps professionals on AWS.

What you will learn:

● Create repeatable training workflows to accelerate model development

● Catalog ML artifacts centrally for model reproducibility and governance

● Integrate ML workflows with CI/CD pipelines for faster time to production

● Continuously monitor data and models in production to maintain quality

● Optimize model deployment for performance and cost

Who this book is for:

This book suits ML engineers, DevOps engineers, software developers, architects, and team leaders aspiring to be MLOps professionals on AWS.

商品描述(中文翻譯)

本書專注於在生產環境中部署、測試、監控和自動化機器學習（ML）系統。內容涵蓋 AWS MLOPS 工具，如 Amazon SageMaker、Data Wrangler 和 AWS Feature Store，以及在 AWS 上運行 ML 系統的最佳實踐。

本書解釋了如何利用 AWS 雲端的良好架構支柱設計、開發和大規模部署 ML 工作負載。首先介紹 AWS 服務和 MLOps 工具，並設置 MLOps 環境。內容包括運營卓越性，涵蓋 CI/CD 管道和基礎設施即代碼（Infrastructure as code）。討論了 MLOps 中的安全性、數據隱私、IAM 以及通過自動化測試來提高可靠性。還探討了性能效率和成本優化，例如適當調整 ML 資源的大小。書末總結了 MLOps 的最佳實踐、針對 GenAI 的 MLOps、新興趨勢以及 MLOps 的未來發展。

到最後，讀者將學會如何在 AWS 雲端上運行 ML 工作負載。本書適合希望成為 AWS 上 MLOps 專業人士的軟體開發人員、ML 工程師、DevOps 工程師、架構師和團隊領導者。

您將學到的內容：
- 創建可重複的訓練工作流程以加速模型開發
- 中央管理 ML 藝術品以實現模型的可重現性和治理
- 將 ML 工作流程與 CI/CD 管道整合，以縮短生產時間
- 持續監控生產中的數據和模型以維持質量
- 優化模型部署以提高性能和降低成本

本書的對象：
本書適合希望成為 AWS 上 MLOps 專業人士的 ML 工程師、DevOps 工程師、軟體開發人員、架構師和團隊領導者。

作者簡介

Neel Sendas is a Principal Technical Account Manager at Amazon Web Services (AWS). In this role, he serves as the AWS Cloud Operations lead for some of the largest enterprises that utilize AWS services. Drawing from his expertise in cloud operations, in this book, Neel presents solutions to common challenges related to ML Cloud Governance, Cloud Finance, and Cloud Operational Resilience & Management at scale. Neel also plays a crucial role as part of the core team of Machine Learning Technical Field Community leaders at AWS, where he contributes to shaping the roadmap of AWS Artificial Intelligence and Machine Learning (AI/ML) Services. Neel is based in the state of Georgia, United States.

Deepali Rajale is a former AWS ML Specialist Technical Account Manager, with extensive experience supporting enterprise customers in implementing MLOps best practices across various industries. She is also the founder of Karini AI, a company dedicated to democratizing generative AI for businesses. She enjoys blogging about ML and Generative AI and coaching customers to optimize their AI/ML workloads for operational efficiency and cost optimization. In her spare time, she enjoys traveling, seeking new experiences, and keeping up with the latest technology trends.

作者簡介(中文翻譯)

Neel Sendas 是亞馬遜網路服務（AWS）的首席技術客戶經理。在這個角色中，他擔任一些使用 AWS 服務的大型企業的 AWS 雲端運營負責人。根據他在雲端運營方面的專業知識，Neel 在本書中提出了與機器學習雲端治理、雲端財務以及大規模雲端運營韌性與管理相關的常見挑戰的解決方案。Neel 也是 AWS 機器學習技術領域社群核心團隊的重要成員，為 AWS 人工智慧和機器學習（AI/ML）服務的路線圖貢獻力量。Neel 目前居住在美國喬治亞州。

Deepali Rajale 是前 AWS 機器學習專家技術客戶經理，擁有豐富的經驗，支持企業客戶在各行各業實施 MLOps 最佳實踐。她也是 Karini AI 的創始人，該公司致力於為企業普及生成式 AI。她喜歡撰寫有關機器學習和生成式 AI 的部落格，並指導客戶優化其 AI/ML 工作負載，以提高運營效率和成本優化。在空閒時間，她喜歡旅行、尋求新體驗，並跟上最新的科技趨勢。

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