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Structuring Azure ML Projects and using the Terminal

Tomaz Kastrun nears the end of the Azure ML advent. Day 20 covers package requirements and other niceties:

When creating notebooks, it is always a good way to have the dependencies included. Whether it is a particular version of a package, a separate script file or an installation requirement.

Selecting an environment or kernel can be an issue if it is not correctly initiated with the code. And you can also check the kernels with a simple python code:

Day 21 looks at the Azure CLI and running code from within a compute instance terminal:

Using Azure CLI can help you progress faster, make repetitve tasks automated and even use the GIT integration, for faster and better collaboration.

So we have created a YAML file on Day20 and we can use it also with Azure CLI to create an environment.