Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

An IT department creates the following Azure resource groups and resources:

The IT department creates an Azure Kubernetes Service (AKS)-based inference compute target named aks-cluster in the Azure Machine Learning workspace.

You have a Microsoft Surface Book computer with a GPU. Python 3.6 and Visual Studio Code are installed.

You need to run a script that trains a deep neural network (DNN) model and logs the loss and accuracy metrics.

Solution: Install the Azure ML SDK on the Surface Book. Run Python code to connect to the workspace and then run the training script as an experiment on local compute.

You are working on a classification task. You have a dataset indicating whether a student would like to play soccer and associated attributes. The dataset includes the following columns:

You need to classify variables by type.

Which variable should you add to each category? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

You use Azure Machine Learning Designer to load the following datasets into an experiment:

Dataset1

Dataset2

You use Azure Machine Learning Designer to load the following datasets into an experiment:

You need to create a dataset that has the same columns and header row as the input datasets and contains all rows from both input datasets.

Solution: Use the Join Data component.

Does the solution meet the goal?