Lab 1 - AML Workspace Setup
Create a Azure Machine Learning Workspace
To get started we need to setup a few resources in Azure. Please follow this guide to setup your dev environment.
Create a resource group
The Azure Machine Learning workspace must be created inside a resource group. You can use an existing resource group or create a new one. To create a new resource group, use the following command. Replace with the name to use for this resource group. Replace with the Azure region to use for this resource group:
Example name and location:
resource group name: pytorchworkshop
location: WestEurope or eastus
Location: Choose eastus or WestEurope, this is needed for the compute we are using later.
Create the Azure Machine Learning Workspace
To create a new workspace where the services are automatically created, use the following command:
If the az ml command does not work run: az extension add -n ml -y
You can now view your workspace by visiting https://ml.azure.com
Make things easier
After every az ml command you have to type "-w <workspace-name> -g <resource-group-name>". You can make everything a bit easier by settings the values for this parameters by default.
Create a Compute Cluster
To train our model we need an Azure Machine Learning Compute cluster. To create a new compute cluster, use the following command.
This command will create an Azure Machine Learning Compute cluster with 1 node that is always on and is using STANDARD_NC6 virtual Machines.
To speed up the training process you can use a GPU enabled NC6 machine
View your created Azure Machine Learning Compute cluster on https://ml.azure.com
Creating compute can take a few minutes to complete
To see the list of created compute in your workspace you can type:
Setup completed
The setup of your workspace with compute is now completed
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