What should you do?

You use the Azure Machine Learning Python SDK to define a pipeline to train a model.

The data used to train the model is read from a folder in a datastore.

You need to ensure the pipeline runs automatically whenever the data in the folder changes.

What should you do?
A . Set the regenerate_outputs property of the pipeline to True
B . Create a ScheduleRecurrance object with a Frequency of auto. Use the object to create a Schedule for the pipeline
C . Create a PipelineParameter with a default value that references the location where the training data is stored
D . Create a Schedule for the pipeline. Specify the datastore in the datastore property, and the folder containing the training data in the path_on_datascore property

Answer: D

Explanation:

Reference: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-trigger-published-pipeline