You have a Python script named train.py in a local folder named scripts. The script trains a regression model using scikit-learn and includes code to load a training data file from the same scripts folder.

You must run the script as an Azure ML experiment on a compute cluster named aml-compute. You need to configure the run to ensure the environment includes the required packages for model training. You have instantiated a variable named aml_compute that references the target compute cluster.

Solution: Run the following code:

from azureml.core import ScriptRunConfig, Experiment

src = ScriptRunConfig(source_directory='scripts',
                      script='train.py',
                      compute_target=aml_compute)
run_config = src.run_config
run_config.environment.python.conda_dependencies = 'scikit-learn'
experiment = Experiment(workspace=ws, name='train-experiment')
run = experiment.submit(config=src)

from azureml.core import ScriptRunConfig, Experiment

src = ScriptRunConfig(source_directory='scripts',
                      script='train.py',
                      compute_target=aml_compute)
run_config = src.run_config
run_config.environment.python.conda_dependencies = 'scikit-learn'
experiment = Experiment(workspace=ws, name='train-experiment')
run = experiment.submit(config=src)

Does the solution meet the goal?