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Tutorial: Kubeflow End-to-End: GitHub Issue Summarization - Michelle Casbon & Amy Unruh, Google (Limited Seating Available - See Description for Details)
Kubeflow is an OSS machine learning stack that runs on Kubernetes.In this session, you will learn how to install and use Kubeflow to support a full ML workflow.You'll build an automatic summary generator using a public dataset of GitHub Issues. In the process, you'll install Kubeflow from scratch, preprocess your dataset, then perform training of a TensorFlow NLP model. You'll then evaluate your trained model, serve it, and interact with the prediction endpoint from a web front-end.You will become familiar with Google Cloud Platform and OSS tools and services such as Apache Beam, TFX, Cloud Shell, Kubernetes Engine, Cloud Storage, and Container Registry. All components are built from source in the Kubeflow Examples repository and are directly transferable to other environments (local, on-prem, and other cloud providers).Prerequisite: familiarity with Kubernetes.
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