What should you do?

You plan to run a script as an experiment using a Script Run Configuration. The script uses modules from the scipy library as well as several Python packages that are not typically installed in a default conda environment.

You plan to run the experiment on your local workstation for small datasets and scale out the experiment by running it on more powerful remote compute clusters for larger datasets.

You need to ensure that the experiment runs successfully on local and remote compute with the least administrative effort.

What should you do?
A . Do not specify an environment in the run configuration for the experiment. Run the experiment by using the default environment.
B . Create a virtual machine (VM) with the required Python configuration and attach the VM as a compute target. Use this compute target for all experiment runs.
C . Create and register an Environment that includes the required packages. Use this Environment for all experiment runs.
D . Create a config.yaml file defining the conda packages that are required and save the file in the experiment folder.
E . Always run the experiment with an Estimator by using the default packages.

View Answer

Answer: C

Explanation:

If you have an existing Conda environment on your local computer, then you can use the service to create an environment object. By using this strategy, you can reuse your local interactive environment on remote runs.

Reference: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-use-environments