Microsoft (DP-100) Exam Questions And Answers page 2
You are developing a data science workspace that uses an Azure Machine Learning service.
You need to select a compute target to deploy the workspace.
What should you use?
You need to select a compute target to deploy the workspace.
What should you use?
Designing and Implementing Data Science Solutions
Deployment and Monitoring
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?
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?
Data Preparation and Processing
Modeling
You have an Azure Machine Learning workspace that contains a CPU-based compute cluster and an Azure Kubernetes Service (AKS) inference cluster. You create a tabular dataset containing data that you plan to use to create a classification model.
You need to use the Azure Machine Learning designer to create a web service through which client applications can consume the classification model by submitting new data and getting an immediate prediction as a response.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
You need to use the Azure Machine Learning designer to create a web service through which client applications can consume the classification model by submitting new data and getting an immediate prediction as a response.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Data Preparation and Processing
Modeling
You create a binary classification model by using Azure Machine Learning Studio.
You must tune hyperparameters by performing a parameter sweep of the model. The parameter sweep must meet the following requirements:
• iterate all possible combinations of hyperparameters
• minimize computing resources required to perform the sweep
You need to perform a parameter sweep of the model.
Which parameter sweep mode should you use?
You must tune hyperparameters by performing a parameter sweep of the model. The parameter sweep must meet the following requirements:
• iterate all possible combinations of hyperparameters
• minimize computing resources required to perform the sweep
You need to perform a parameter sweep of the model.
Which parameter sweep mode should you use?
Data Preparation and Processing
Modeling
You have the following code. The code prepares an experiment to run a script:
The experiment must be run on local computer using the default environment.
You need to add code to start the experiment and run the script.
Which code segment should you use?
The experiment must be run on local computer using the default environment.
You need to add code to start the experiment and run the script.
Which code segment should you use?
Data Preparation and Processing
Deployment and Monitoring
You are preparing to use the Azure ML SDK to run an experiment and need to create compute. You run the following code:
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Data Preparation and Processing
Deployment and Monitoring
This question is included in a number of questions that depicts the identical set-up. However, every question has a distinctive result. Establish if the recommendation satisfies the requirements.
You have been tasked with evaluating your model on a partial data sample via k-fold cross-validation.
You have already configured a k parameter as the number of splits. You now have to configure the k parameter for the cross-validation with the usual value choice.
Recommendation: You configure the use of the value k=10.
Will the requirements be satisfied?
You have been tasked with evaluating your model on a partial data sample via k-fold cross-validation.
You have already configured a k parameter as the number of splits. You now have to configure the k parameter for the cross-validation with the usual value choice.
Recommendation: You configure the use of the value k=10.
Will the requirements be satisfied?
Data Preparation and Processing
Modeling
You create a binary classification model.
You need to evaluate the model performance.
Which two metrics can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
You need to evaluate the model performance.
Which two metrics can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Modeling
Deployment and Monitoring
You create a binary classification model to predict whether a person has a disease.
You need to detect possible classification errors.
Which error type should you choose for each description? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You need to detect possible classification errors.
Which error type should you choose for each description? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Data Preparation and Processing
Modeling
You are creating a machine learning model. You have a dataset that contains null rows.
You need to use the Clean Missing Data module in Azure Machine Learning Studio to identify and resolve the null and missing data in the dataset.
Which parameter should you use?
You need to use the Clean Missing Data module in Azure Machine Learning Studio to identify and resolve the null and missing data in the dataset.
Which parameter should you use?
Data Preparation and Processing
Modeling
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