Which two components can you drag onto a canvas in Azure Machine Learning designer? Each correct answer presents a complete solution.
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A. B. C. D.AD
You can drag-and-drop datasets and modules onto the canvas.
https://docs.microsoft.com/en-us/azure/machine-learning/concept-designerIn Azure Machine Learning designer, you can drag components onto a canvas to create machine learning workflows. The components are represented by nodes on the canvas and are connected to form a pipeline.
The four types of components that you can use in Azure Machine Learning designer are:
Dataset: A dataset is a collection of data that you can use as input to a machine learning model. You can use datasets to represent your training data, validation data, or test data. When you drag a dataset onto the canvas, you can configure it to read data from various sources, such as Azure Blob storage, Azure Data Lake Storage, or a web URL.
Compute: A compute target is a resource that you can use to run your machine learning workflows. You can use compute targets to specify where your training job will run, such as on a local machine, in a cloud-based virtual machine, or in a Kubernetes cluster. When you drag a compute node onto the canvas, you can configure it to use various compute targets, such as Azure Machine Learning compute, Azure Batch AI, or Azure Kubernetes Service.
Pipeline: A pipeline is a sequence of steps that you can use to build and deploy a machine learning model. You can use pipelines to automate your machine learning workflows, from data preparation to model training and deployment. When you drag a pipeline node onto the canvas, you can define the steps in the pipeline, such as data ingestion, data transformation, feature engineering, model training, and model evaluation.
Module: A module is a reusable piece of code that you can use to perform a specific task in your machine learning workflow. You can use modules to build complex pipelines by chaining together multiple modules. When you drag a module onto the canvas, you can choose from a library of pre-built modules, such as data transformations, model trainers, and evaluators.
Therefore, the two components that you can drag onto a canvas in Azure Machine Learning designer are:
Hence, the correct answer is A. dataset and D. module.