Distributed TensorFlow using Kubernetes
Distributed TensorFlow using Kubernetes


In this session, attendees will learn about operationalizing TensorFlow Object Detection API using cloud services and Kubernetes.
First part will cover TensorFlow Object Detection API and how-to setup our training and evaluation workflow using Docker containers and virtual machines.

After that, attendees will learn about how to train and scale using Kubernetes and distributed TensorFlow.
Finally, session will cover how we can serve our trained model using TensorFlow Serving as a web service, and we will be deploying a simple client to get results from our service.


Rita Zhang is a Software Engineer at Microsoft, based in San Francisco. She spends most of her days contributing to various open source projects while working with Azure engineering teams and customers using cloud native technologies. Rita is passionate about open source, running distributed workloads at scale, and all things dogs. She has a bachelor of science degree in EECS from UC Berkeley.

Open Data Science




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