Shanghai, China
June 24–26, 2019
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Wednesday, June 26 • 12:05 - 12:40
Using Kubernetes for Machine Learning Frameworks - Arun Gupta, AWS

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Kubernetes provides isolation, auto-scaling, load balancing, flexibility and GPU support. These features are critical to run computationally, data intensive and hard to parallelize ML models. Declarative syntax of Kubernetes deployment descriptors make it easy for non-operationally focused engineers to easily train ML models on Kubernetes. This talk will explain why and how Kubernetes is well suited for single and multi node distributed training, deploying your ML models in production and setting up visualization tools like TensorBoard for monitoring. Specifically it will show how to setup a variety of open source ML frameworks such as TensorFlow, Apache MXNet and Pytorch on a Kubernetes cluster. The attendees will learn distributed training, massaging and inference phases of setting up a ML framework on Kubernetes. Attendees will leave with a GitHub repo of fully working samples.

avatar for Arun Gupta

Arun Gupta

Sr Engineering Manager, Apple
Arun Gupta is a Senior Engineering Manager at Apple. He is responsible for the open source strategy at Apple, and participates at CNCF Board and technical meetings actively. He has extensive experience in building, growing, and engaging with communities using collaboration and passion... Read More →

Wednesday June 26, 2019 12:05 - 12:40 CST