Which two components can you drag onto a canvas in Azure Machine Learning designer? Each correct answer presents a complete solution. NOTE: Each…

Azure Machine Learning designer provides a visual, drag-and-drop interface for building machine learning pipelines. The fundamental building blocks that you work with on the designer canvas are datasets and modules (also known as components). You start by dragging a registered dataset onto the canvas to provide the data. Then, you drag various modules from the asset library, which represent data processing tasks, algorithms, and evaluation functions, and connect them to the dataset and each other to define the workflow.

B. compute: A compute target is the resource where the pipeline executes. It is selected in the pipeline job's settings pane, not dragged onto the canvas as a workflow step.

C. pipeline: A pipeline is the complete workflow that you construct on the canvas by connecting datasets and modules. It is the output of the design process, not an input component to be dragged onto it.

1. Microsoft Learn

"What is Azure Machine Learning designer?"

Reference: In the "Designer workflow" section

the documentation states: "You build a pipeline in the designer by dragging and dropping datasets and components onto the canvas." (Note: 'Components' is the newer term for 'modules').

2. Microsoft Learn

"Tutorial: Predict automobile price with the designer (v2)"

Reference: Under the section "Create a new pipeline

" Step 4 explicitly instructs: "Drag the Automobile price data (Raw) dataset onto the canvas." This confirms that datasets are dragged onto the canvas.

3. Microsoft Learn

"Tutorial: Predict automobile price with the designer (v2)"

Reference: Under the section "Clean the data

" Step 1 instructs: "In the component palette to the left of the canvas...find the Select Columns in Dataset component. Drag the component onto the canvas." This confirms that modules/components are dragged onto the canvas.