Preparing the Azure Machine Learning Workspace (Part 2 of 2)

By Ashwin Venugopal -

 




To read part 1, please click here




Deploying the Workspace

We can easily set up our first Azure Machine Learning workspace with the help of CLI, as follows:
  • Log in to your Azure environment via the CLI- $ az login, that will open a website with an AAD login screen, and when you return to the console, you will have some information about your AAD tenant, your subscription, as well as your user.

  • However, if you want to check which subscription is active (for more that one subscription), you can use $ az account show --output table command. 

  • Now, after being done with all that, you have to check the situation with the installed extension via $ az extension list command.

  • You should also remove the old version carefully, so that you won't break a script still in use. To do this, you can use $ az extension remove -n azure-cli-ml; or $ az extension remove -n ml commands.

  • Now, you can install the ML extension via  $ az extension add -n ml command,

  • You can look at the help page for the extension  ($ az ml -h).

  • You can also check if anything is missing for the creation of the workspace via  $ az ml workspace create -h command.

  • Now, as a resource group is required which in turn also require a location, we have to look for an available data center location for the Azure cloud with the help of  $ az account list-locations -o table command, which can be used to create the resource group.

  • Finally, if you want to check the deployment at any point, then, you can run $ az ml workspace show -g mldemo -w ml demows command.   








To read part 1, please click here




















































































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