Question

Your team has an existing Python training script that trains a scikit-learn regression model and logs metrics with MLflow. You need to run this script on an Azure Machine Learning compute cluster as a reproducible job, passing a registered data asset and a learning-rate argument, while ensuring the run appears in a specific experiment for later comparison. Which Azure Machine Learning job type should you configure?

Accepted Answer

A command job that specifies the script, compute target, environment, inputs, and experiment_name

Answer

An AutoML job configured for the regression task with the data asset as training data

Answer

A sweep job referencing the script with a search space defined over the learning-rate argument

Answer

A pipeline job containing a single parallel component that maps over the data asset