HOTSPOT -You write code to retrieve an experiment that is run from your Azure Machine Learning workspace.The run used the model interpretation support in Azure Machine Learning to generate and upload a model explanation.Business managers in your organization want to see the importance of the features in the model.You need to print out the model features and their relative importance in an output that looks similar to the following.How should you complete the code? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point.Hot Area:
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.You are using Azure Machine Learning to run an experiment that trains a classification model.You want to use Hyperdrive to find parameters that optimize the AUC metric for the model. You configure a HyperDriveConfig for the experiment by running the following code:You plan to use this configuration to run a script that trains a random forest model and then tests it with validation data. The label values for the validation data are stored in a variable named y_test variable, and the predicted probabilities from the model are stored in a variable named y_predicted.You need to add logging to the script to allow Hyperdrive to optimize hyperparameters for the AUC metric.Solution: Run the following code:Does the solution meet the goal?
You create a deep learning model for image recognition on Azure Machine Learning service using GPU-based training.You must deploy the model to a context that allows for real-time GPU-based inferencing.You need to configure compute resources for model inferencing.Which compute type should you use?
HOTSPOT-You plan to implement an Azure Machine Learning solution.You have the following requirements:• Run a Jupyter notebook to interactively train a machine learning model.• Deploy assets and workflows for machine learning proof of concept by using scripting rather than custom programming.You need to select a development technique for each requirement.Which development technique should you use? To answer, select the appropriate options in the answer area.NOTE: Each correct selection is worth one point.
You need to visually identify whether outliers exist in the Age column and quantify the outliers before the outliers are removed.Which three Azure Machine Learning Studio modules should you use? Each correct answer presents part of the solution.NOTE: Each correct selection is worth one point.
You need to implement a scaling strategy for the local penalty detection data.Which normalization type should you use?
