Christopher Cho demonstrates how Kubernetes can be easily leveraged to build a complete deep learning pipeline, including data ingestion and aggregation, preprocessing, ML training, and serving with the mighty Kubernetes APIs. Along the way, Chistopher covers Kubeflow, Google’s open source solution for managing machine learning with TensorFlow in a portable, scalable manner, and shares recent innovations in monitoring GPUs with Kubernetes, smarter serving with GPUs, autoscaling from and to zero instances, and a declarative approach to portable distributed training.
Join in to learn how to get started with just three commands across a variety of platforms with Kubernetes and Kubeflow.
Christopher Cho is a product manager and cloud program manager at Google, where he helps customers solve machine learning and infrastructure problems, and is one of the product managers in Kubeflow team. Previously, Chris was research program manager at DeepMind, working on cutting-edge ML research. His background is in enterprise business consulting. Chris is currently working toward his MSCS at Georgia Tech. He holds a BS in mechanical engineering from the University of Illinois Urbana-Champaign.
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