Hotspot Question
You manage an Azure Machine Learning workspace by using the Python SDK v2.
You must create an automated machine learning job to generate a classification model by using data files stored in Parquet format.
You must configure an autoscaling compute target and a data asset for the job.
You need to configure the resources for the job.
Which resource configuration should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation:
Compute target: Azure Databricks
This is because Azure Databricks supports autoscaling of workers required to run your job, which dynamically reallocates workers to match the computational demands of your job, thereby achieving high cluster utilization without the need for provisioning the cluster to match a specific workload.
Data asset: uri_folder
This option allows the machine learning job to access all the Parquet files stored in the specified directory. If you have multiple Parquet data files, you would use a URI that points to a folder containing all these files.