This template deploy a Ubuntu Server with some tools for Data Science. You can provide the username, password, virtual machine name and select between CPU or GPU computing.
This Azure Resource Manager (ARM) template was created by a member of the community and not by Microsoft. Each ARM template is licensed to you under a licence agreement by its owner, not Microsoft. Microsoft is not responsible for ARM templates provided and licensed by community members and does not screen for security, compatibility or performance. Community ARM templates are not supported under any Microsoft support programme or service and are made available AS IS without warranty of any kind.
|adminUsername||Username for Administrator Account|
|vmName||The name of you Virtual Machine.|
|location||Location for all resources.|
|cpu-gpu||Choose between CPU or GPU processing|
|virtualNetworkName||Name of the VNET|
|subnetName||Name of the subnet in the virtual network|
|networkSecurityGroupName||Name of the Network Security Group|
|authenticationType||Type of authentication to use on the Virtual Machine. SSH key is recommended.|
|adminPasswordOrKey||SSH Key or password for the Virtual Machine. SSH key is recommended.|
Use the template
New-AzResourceGroup -Name <resource-group-name> -Location <resource-group-location> #use this command when you need to create a new resource group for your deploymentInstall and configure Azure PowerShell
New-AzResourceGroupDeployment -ResourceGroupName <resource-group-name> -TemplateUri https://raw.githubusercontent.com/Azure/azure-quickstart-templates/master/application-workloads/datascience/vm-ubuntu-DSVM-GPU-or-CPU/azuredeploy.json
az group create --name <resource-group-name> --location <resource-group-location> #use this command when you need to create a new resource group for your deploymentInstall and Configure the Azure Cross-Platform Command-Line Interface
az group deployment create --resource-group <my-resource-group> --template-uri https://raw.githubusercontent.com/Azure/azure-quickstart-templates/master/application-workloads/datascience/vm-ubuntu-DSVM-GPU-or-CPU/azuredeploy.json