You create an Azure Machine Learning dataset containing automobile price data The dataset includes 10,000 rows and 10 columns You use Azure Machine Learning Designer to transform the dataset by using an Execute Python Script component and custom code.
The code must combine three columns to create a new column.
You need to configure the code function.
Which configurations should you use? lo answer, select the appropriate options in the answer area NOTE: Each correct selection is worth one point.

You have an Azure Machine Learning workspace. You are running an experiment on your local computer.
You need to ensure that you can use MLflow Tracking with Azure Machine Learning Python SDK v2 to store metrics and artifacts from your local experiment runs in the workspace.
In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.

You have a Python script that executes a pipeline. The script includes the following code:
from azureml.core import Experiment
pipeline_run = Experiment(ws, 'pipeline_test').submit(pipeline)
You want to test the pipeline before deploying the script.
You need to display the pipeline run details written to the STDOUT output when the pipeline completes.
Which code segment should you add to the test script?

You use Azure Machine Learning designer to create a training pipeline for a regression model.
You need to prepare the pipeline for deployment as an endpoint that generates predictions asynchronously for a dataset of input data values.
What should you do?

You are analyzing a dataset containing historical data from a local taxi company. You arc developing a regression a regression model.
You must predict the fare of a taxi trip.
You need to select performance metrics to correctly evaluate the- regression model.
Which two metrics can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.