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README.md		README.md
requirements.txt		requirements.txt
setup_a_kubeflow_cluster.md		setup_a_kubeflow_cluster.md
teardown.md		teardown.md

README.md

[WIP] End-to-End kubeflow tutorial using a Sequence-to-Sequence model

This example demonstrates how you can use kubeflow end-to-end to train and serve a Sequence-to-Sequence model on an existing kubernetes cluster. This tutorial is based upon @hamelsmu's article "How To Create Data Products That Are Magical Using Sequence-to-Sequence Models".

Goals

There are two primary goals for this tutorial:

End-to-End kubeflow example
End-to-End Sequence-to-Sequence model

By the end of this tutorial, you should learn how to:

Setup a Kubeflow cluster on an existing Kubernetes deployment
Spawn up a Jupyter Notebook on the cluster
Spawn up a shared-persistent storage across the cluster to store large datasets
Train a Sequence-to-Sequence model using TensorFlow on the cluster using GPUs
Serve the model using TensorFlow Serving

Steps: