You use the Azure Machine learning SDK foe Python to create a pipeline that includes the following step:

The output of the step run must be cached and reused on subsequent runs when the source.directory value has not changed.

You need to define the step.

What should you include in the step definition?

You have an Azure Machine Learning workspace and a data source file ./data/cc_data.csv in the local storage.

You plan to use Azure Machine Learning Python SDK v2 to store the content of the cc.data.csv file in a data asset named cc_data_asset in the workspace.

You write code to connect to the workspace and import all required libraries.

You need to complete the remaining code to ensure it will result in the cc_data_asset that contains the data from cc_data.csv.

How should you complete the code? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

You are planning to register a trained model in an Azure Machine Learning workspace.

You must store additional metadata about the model in a key-value format. You must be able to add new metadata and modify or delete metadata after creation.

You need to register the model.

Which parameter should you use?