Using Kubernetes for Machine Learning Frameworks • Arun Gupta • GOTO 2019

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This presentation was recorded at GOTO Chicago 2019. #gotocon #gotochgo http://gotochgo.com Arun Gupta - Principal Open Source Technologist at AWS and CNCF Board Member ABSTRACT Kubernetes provides isolation, auto-scaling, load balancing, flexibility and GPU support. These features are critical to run computationally and data intensive and hard to parallelize machine learning models. Declarative syntax of Kubernetes deployment descriptors make it easy for non-operationally focused engineers to easily train machine learning models on Kubernetes. This talk will explain why and how Kubernetes is well suited for training and running your machine learning models in production. Specifically it will show how to setup a variety of open source machine learning frameworks such as TensorFlow, Apache MXNet and Pytorch on a Kubernetes cluster. Attendees will learn training, massaging and inference phases of setting up a Machine Learning framework on Kubernetes. Attendees [...] Download slides and read the full abstract here: https://gotochgo.com/2019/sessions/696 RECOMMENDED BOOKS Holden Karau, Trevor Grant, Boris Lublinsky, Richard Liu & Ilan Filonenko • Kubeflow for Machine Learning • https://amzn.to/3JVngcx Liz Rice • Container Security • https://amzn.to/3oU4iJe Liz Rice • Kubernetes Security • https://www.oreilly.com/library/view/kubernetes-security/9781492039075 Brendan Burns, Joe Beda & Kelsey Hightower • Kubernetes: Up and Running • https://amzn.to/3wrtwlp John Arundel & Justin

Published 2019-06-26 · Watch on YouTube ↗
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