Learn how to build machine learning pipelines in Azure Machine Learning Workspaces using Azure Machine Learning Designer. Drag-and-drop dataset and module components onto a canvas to create a pipeline visually. Classic prebuilt components (v1) and custom components (v2) are NOT compatible. Use custom components for new projects since they are compatible with AzureML V2 and will continue to receive new updates.
Which two components can you drag onto a canvas in Azure Machine Learning designer? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.
You can drag-and-drop datasets and modules onto the canvas.
The two components that can be dragged onto a canvas in Azure Machine Learning designer are dataset and module. The correct answer is A and D.
Azure Machine Learning designer is a drag-and-drop UI interface for building machine learning pipelines in Azure Machine Learning Workspaces. You can build a pipeline visually by dragging and dropping building blocks and connecting them. Note that Designer supports two types of components, classic prebuilt components (v1) and custom components (v2). These two types of components are NOT compatible. Classic prebuilt components support typical data processing and machine learning tasks including regression and classification. Though classic prebuilt components will continue to be supported, no new components will be added. Custom components allow you to wrap your own code as a component enabling sharing across workspaces and seamless authoring across the Azure Machine Learning Studio, CLI v2, and SDK v2 interfaces. For new projects, we highly recommend that you use custom components since they are compatible with AzureML V2 and will continue to receive new updates.
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