In Azure Machine Learning studio, what can you use to author regression machine learning pipelines using a drag-and-drop interface? NotebooksAutomated machine learningDesigner

You need to create a new pipeline to train a regression model using Azure ML Designer. You ingest your data for the model and drop it on the canvas. What module would you typically drag-and-drop next on the canvas?Response: Select Columns in Dataset Train ModelClean Missing dataNormalize DataSplit Data

What does automated machine learning in Azure Machine Learning enable you to do? Automatically deploy new versions of a model as they're trainedAutomatically provision Azure Machine Learning workspaces for new data scientists in an organizationAutomatically run multiple training jobs using different algorithms and parameters to find the best model

. You use Azure Machine Learning designer to create a training pipeline for a classification model. What must you do before deploying the model as a service? Create an inference pipeline from the training pipelineAdd an Evaluate Model module to the training pipelineClone the training pipeline with a different name

4. What does automated machine learning in Azure Machine Learning enable you to do? Automatically deploy new versions of a model as they're trainedAutomatically provision Azure Machine Learning workspaces for new data scientists in an organizationAutomatically run multiple training jobs using different algorithms and parameters to find the best model

You need to evaluate a classification model. Which metric can you use? ​​ Mean squared error (MSE)PrecisionSilhouette3. In deep learning, what is the purpose of a loss function? To remove data for which no known label values are providedTo evaluate the aggregate difference between predicted and actual label valuesTo calculate the cost of training a neural network rather than a statistical model4. What does automated machine learning in Azure Machine Learning enable you to do? Automatically deploy new versions of a model as they're trainedAutomatically provision Azure Machine Learning workspaces for new data scientists in an organizationAutomatically run multiple training jobs using different algorithms and parameters to find the best model