Build a Machine Learning Platform (From Scratch)

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Beschreibung

<b>Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.</b><br><br>Delivering a successful machine learning project is hard. This book makes it easier. In it, you’ll design a reliable ML system from the ground up, incorporating MLOps and DevOps along with a stack of proven infrastructure tools including Kubeflow, MLFlow, BentoML, Evidently, and Feast.<br><br>A properly designed machine learning system streamlines data workflows, improves collaboration between data and operations teams, and provides much-needed structure for both training and deployment. In this book you’ll learn how to design and implement a machine learning system from the ground up. You’ll appreciate this instantly-useful introduction to achieving the full benefits of automated ML infrastructure.<br><br>In <i>Machine Learning Platform Engineering</i> you’ll learn how to:<ul><li>Set up an MLOps platform</li><li>Deploy machine learning models to production</li><li>Build end-to-end data pipelines</li><li>Effective monitoring and explainability</li></ul><b>About the technology</b><br><br>AI and ML systems have a lot of moving parts, from language libraries and application frameworks, to workflow and deployment infrastructure, to LLMs and other advanced models. A well-designed internal development platform (IDP) gives developers a defined set of tools and guidelines that accelerate the dev process, improving consistency, security, and developer experience.<br><br><b>About the book</b><br><br><i>Machine Learning Platform Engineering</i> shows you how to build an effective IDP for ML and AI applications. Each chapter illuminates a vital part of the ML workflow, including setting up orchestration pipelines, selecting models, allocating resources for training, inference, and serving, and more. As you go, you’ll create a versatile modern platform using open source t

Artikeldetails

EAN

9781633437333

Sprache

Englisch

Einband / Art

Buch

Maße

235 x 192 x 40 mm

Erscheinungsjahr

2026

Verlag / Hersteller

Manning Publications