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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 a Tornado Server