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Building models is a small part of the story when it comes to deploying machine learning applications.
Authors Josh Patterson.
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.
The entire process involves developing, orchestrating, deploying, and running scalable and portable machine learning workloads--a process Kubeflow makes much easier.
Building models is a small part of the story when it comes to deploying machine learning applications
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