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portada Essential Kubeflow: Engineering ML Workflows on Kubernetes
Type
Physical Book
Publisher
Author
Language
English
Pages
250
Format
Paperback
ISBN13
9780443452543

Essential Kubeflow: Engineering ML Workflows on Kubernetes

Josyula, Prashanth; Arora, Sonika; Kumar, Anant (Author) · Morgan Kaufmann Publishers · Paperback

Essential Kubeflow: Engineering ML Workflows on Kubernetes - Josyula, Prashanth; Arora, Sonika; Kumar, Anant

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Delivery: 22 Sep - 25 Sep Shipping: 11 to 13 business days.
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Synopsis "Essential Kubeflow: Engineering ML Workflows on Kubernetes"

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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