Train TensorFlow Models at Scale with Kubernetes on Azure

Prerequisites

Have a valid Microsoft Azure subscription allowing the creation of an ACS cluster
Docker client installed: Installing Docker
Azure-cli (2.0) installed: Installing the Azure CLI 2.0 | Microsoft Docs
Git cli installed: Installing Git CLI
Kubectl installed: Installing Kubectl
Helm installed: Installing Helm CLI (Note: On Windows you can extract the tar file using a tool like 7Zip.

Clone this repository somewhere so you can easily access the different source files:

git clone https://github.com/wbuchwalter/tensorflow-k8s-azure

	Module	Description
0	Introduction	Introduction to this workshop. Motivations and goals.
1	Docker	Docker and containers 101.
2	Kubernetes	Kubernetes important concepts overview.
3	Helm	Introduction to Helm
4	GPUs	How to use GPUs with Kubernetes.
5	TFJob	How to use `tensorflow/k8s` and `TFJob` to deploy a simple TensorFlow training.
6	Distributed Tensorflow	Going distributed with `TFJob`
7	Hyperparameters Sweep with Helm	Using Helm to deploy a large number of training testing different hypothesis, monitoring and comparing them.
8	Going Further	Links and resources to go further: Autoscaling, Distributed Storage.
9	Jupyter Notebooks	Easily deploy a Jupyter Notebook instance on Kubernetes.