Question 1

Which package managers are usually used in the installation of a Python virtual environment? Select all that apply.

Question 2

You saved a specification file named conda.yml and you want to use it to create an Azure ML environment.

Which SDK command does the job?

Question 3

You want to create an Azure ML environment by specifying the packages you need.

Which SDK commands does the job?

from azureml.core import Environment env = Environment('training_environment') deps = CondaDependencies.create(conda_packages=['scikit-learn','pandas','numpy'], pip_packages=['azureml-defaults']) env.python.conda_dependencies = deps

from azureml.core import Environment from azureml.core.conda_dependencies import Conda env = Environment('training_environment') deps = CondaDependencies.create(conda_packages=['scikit-learn','pandas','numpy'], pip_packages=['azureml-defaults']) env.python.conda_dependencies = deps

from azureml.core import Environment from azureml.core.conda_dependencies import CondaDependencies env = Environment('training_environment') deps = CondaDependencies.deploy(conda_packages=['scikit-learn','pandas','numpy'], pip_packages=['azureml-defaults']) env.python.conda_dependencies = deps

from azureml.core import Environment from azureml.core.conda_dependencies import CondaDependencies env = Environment('training_environment') deps = CondaDependencies.create(conda_packages=['scikit-learn','pandas','numpy'], pip_packages=['azureml-defaults']) env.python.conda_dependencies = deps

Question 4

If you are running a notebook experiment on an Azure Machine Learning compute instance, what type of compute are you using?

Question 5

If you have an Azure Databricks cluster that you want to use for experiment running and model training, which type of compute target is this?