January 1, 2020

202 words 1 min read

Why Data Scientists Love Kubernetes

Why Data Scientists Love Kubernetes

This talk will introduce the workflows and concerns of data scientists and machine learning engineers and demonstrate how to make Kubernetes a powerhouse for intelligent applications. Well show how …

Talk Title Why Data Scientists Love Kubernetes
Speakers William Benton (Manager, Software Engineering and Sr. Principal Engineer, Red Hat, Inc), Sophie Watson (Software Engineer, Red Hat, Inc)
Conference KubeCon + CloudNativeCon North America
Conf Tag
Location Seattle, WA, USA
Date Dec 9-14, 2018
URL Talk Page
Slides Talk Slides
Video

This talk will introduce the workflows and concerns of data scientists and machine learning engineers and demonstrate how to make Kubernetes a powerhouse for intelligent applications. We’ll show how community projects like Kubeflow and radanalytics.io support the entire intelligent application development lifecycle. We’ll cover several key benefits of Kubernetes for a data scientist’s workflow, from experiment design to publishing results. You’ll see how well scale-out data processing frameworks like Apache Spark work in Kubernetes. System operators will learn how Kubernetes can support data science and machine learning workflows. Application developers will learn how Kubernetes can enable intelligent applications and cross-functional collaboration. Data scientists will leave with concrete suggestions for how to use Kubernetes and open-source tools to make their work more productive.

comments powered by Disqus