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Kubeflow Operations Guide

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Description: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 platformUnderstand the process of planning your Kubeflow deploymentInstall Kubeflow on an existing on-premises Kubernetes clusterDeploy Kubeflow on Google Cloud Platform step-by-step from the command lineUse the managed Amazon Elastic Kubernetes Service (EKS) to deploy Kubeflow on AWSDeploy and manage Kubeflow across a network of Azure cloud data centers around the worldUse KFServing to develop and deploy machine learning modelsWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Kubeflow Operations Guide. To get started finding Kubeflow Operations Guide, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

Pages: 304

Format: PDF, EPUB & Kindle Edition

Publisher: O'Reilly Media

Release: 2020

ISBN: 1492053244

Description: 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 platformUnderstand the process of planning your Kubeflow deploymentInstall Kubeflow on an existing on-premises Kubernetes clusterDeploy Kubeflow on Google Cloud Platform step-by-step from the command lineUse the managed Amazon Elastic Kubernetes Service (EKS) to deploy Kubeflow on AWSDeploy and manage Kubeflow across a network of Azure cloud data centers around the worldUse KFServing to develop and deploy machine learning modelsWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Kubeflow Operations Guide. To get started finding Kubeflow Operations Guide, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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Kubeflow Operations Guide

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