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Essential Kubeflow: Engineering ML Workflows on Kubernetes

Essential Kubeflow: Engineering ML Workflows on Kubernetes

Paperback

ApplicationsGeneral Computers

ISBN10: 0443452547
ISBN13: 9780443452543
Publisher: Morgan Kaufmann Publishers
Published: Jul 21 2026
Pages: 378
Weight: 2.30
Height: 0.80 Width: 8.40 Depth: 10.90
Language: English
Essential Kubeflow: Engineering ML Workflows on Kubernetes provides the tools needed to transform ML workflows from experimental notebooks to production-ready platforms. Through hands-on examples and production-tested patterns, readers will master essential skills for building enterprise-grade Machine Learning platforms, including architecting production systems on Kubernetes, designing end-to-end ML pipelines, implementing robust model serving, efficiently scaling workloads, managing multi-user environments, deploying automated MLOps workflows, and integrating with existing ML tools. Whether you're a Machine Learning engineer looking to operationalize models, a platform engineer diving into ML infrastructure, or a technical leader architecting ML systems, this book provides solutions for real-world challenges.

With this comprehensive guide to Kubeflow, a widely adopted open source MLOps platforms for automating ML workloads, readers will have the expertise to build and maintain scalable ML platforms that can handle the demands of modern enterprise AI initiatives.

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