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Kubeflow Operations Guide: Managing Cloud and On-Premise...

Kubeflow Operations Guide: Managing Cloud and On-Premise Deployment

Josh Patterson, Michael Katzenellenbogen, Austin Harris
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Building models is a small part of the story when it comes to deploying machine learning applications. The entire process involves developing, orchestrating, deploying, and running scalable and portable machine learning workloads--a process Kubeflow makes much easier. This practical book shows data scientists, data engineers, and platform architects how to plan and execute a Kubeflow project to make their Kubernetes workflows portable and scalable.

Authors Josh Patterson, Michael Katzenellenbogen, and Austin Harris demonstrate how this open source platform orchestrates workflows by managing machine learning pipelines. You'll learn how to plan and execute a Kubeflow platform that can support workflows from on-premises to cloud providers including Google, Amazon, and Microsoft.

  • Dive into Kubeflow architecture and learn best practices for using the platform
  • Understand the process of planning your Kubeflow deployment
  • Install Kubeflow on an existing on-premise Kubernetes cluster
  • Deploy Kubeflow on Google Cloud Platform, AWS, and Azure
  • Use KFServing to develop and deploy machine learning models

年:
2020
出版:
1
出版社:
O'Reilly Media
语言:
english
页:
304
ISBN 10:
1492053279
ISBN 13:
9781492053279
文件:
EPUB, 7.73 MB
IPFS:
CID , CID Blake2b
english, 2020
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