Microsoft (DP-100) Exam Questions And Answers page 27
You are running Python code interactively in a Conda environment. The environment includes all required Azure Machine Learning SDK and MLflow packages.
You must use MLflow to log metrics in an Azure Machine Learning experiment named mlflow-experiment.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You must use MLflow to log metrics in an Azure Machine Learning experiment named mlflow-experiment.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Modeling
Deployment and Monitoring
You are performing a classification task in Azure Machine Learning Studio.
You must prepare balanced testing and training samples based on a provided data set.
You need to split the data with a 0.75:0.25 ratio.
Which value should you use for each parameter? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You must prepare balanced testing and training samples based on a provided data set.
You need to split the data with a 0.75:0.25 ratio.
Which value should you use for each parameter? 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 analyzing the asymmetry in a statistical distribution.
The following image contains two density curves that show the probability distribution of two datasets.
Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.
The following image contains two density curves that show the probability distribution of two datasets.
Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.
Data Preparation and Processing
Modeling
You create an Azure Machine Learning compute target named ComputeOne by using the STANDARD_D1 virtual machine image.
ComputeOne is currently idle and has zero active nodes.
You define a Python variable named ws that references the Azure Machine Learning workspace. You run the following Python 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.
ComputeOne is currently idle and has zero active nodes.
You define a Python variable named ws that references the Azure Machine Learning workspace. You run the following Python 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.
Data Preparation and Processing
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.
An IT department creates the following Azure resource groups and resources:
The IT department creates an Azure Kubernetes Service (AKS)-based inference compute target named aks-cluster in the Azure Machine Learning workspace.
You have a Microsoft Surface Book computer with a GPU. Python 3.6 and Visual Studio Code are installed.
You need to run a script that trains a deep neural network (DNN) model and logs the loss and accuracy metrics.
Solution: Install the Azure ML SDK on the Surface Book. Run Python code to connect to the workspace. Run the training script as an experiment on the aks-cluster compute target.
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.
An IT department creates the following Azure resource groups and resources:
The IT department creates an Azure Kubernetes Service (AKS)-based inference compute target named aks-cluster in the Azure Machine Learning workspace.
You have a Microsoft Surface Book computer with a GPU. Python 3.6 and Visual Studio Code are installed.
You need to run a script that trains a deep neural network (DNN) model and logs the loss and accuracy metrics.
Solution: Install the Azure ML SDK on the Surface Book. Run Python code to connect to the workspace. Run the training script as an experiment on the aks-cluster compute target.
Does the solution meet the goal?
Data Preparation and Processing
Modeling
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 create a model to forecast weather conditions based on historical data.
You need to create a pipeline that runs a processing script to load data from a datastore and pass the processed data to a machine learning model training script.
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 create a model to forecast weather conditions based on historical data.
You need to create a pipeline that runs a processing script to load data from a datastore and pass the processed data to a machine learning model training script.
Solution: Run the following code:
Does the solution meet the goal?
Data Preparation and Processing
Modeling
You train and register a model in your Azure Machine Learning workspace.
You must publish a pipeline that enables client applications to use the model for batch inferencing. You must use a pipeline with a single ParallelRunStep step that runs a Python inferencing script to get predictions from the input data.
You need to create the inferencing script for the ParallelRunStep pipeline step.
Which two functions should you include? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
You must publish a pipeline that enables client applications to use the model for batch inferencing. You must use a pipeline with a single ParallelRunStep step that runs a Python inferencing script to get predictions from the input data.
You need to create the inferencing script for the ParallelRunStep pipeline step.
Which two functions should you include? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Modeling
Deployment and Monitoring
You plan to run a script as an experiment using a Script Run Configuration. The script uses modules from the scipy library as well as several Python packages that are not typically installed in a default conda environment.
You plan to run the experiment on your local workstation for small datasets and scale out the experiment by running it on more powerful remote compute clusters for larger datasets.
You need to ensure that the experiment runs successfully on local and remote compute with the least administrative effort.
What should you do?
You plan to run the experiment on your local workstation for small datasets and scale out the experiment by running it on more powerful remote compute clusters for larger datasets.
You need to ensure that the experiment runs successfully on local and remote compute with the least administrative effort.
What should you do?
Data Preparation and Processing
Deployment and Monitoring
How Can I Reconfigure Azure ML Compute Resource Node Limits?
Multiple Choice
You create an Azure Machine Learning compute resource to train models. The compute resource is configured as follows:
• Minimum nodes: 2
• Maximum nodes: 4
You must decrease the minimum number of nodes and increase the maximum number of nodes to the following values:
• Minimum nodes: 0
• Maximum nodes: 8
You need to reconfigure the compute resource.
What are three possible ways to achieve this goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
• Minimum nodes: 2
• Maximum nodes: 4
You must decrease the minimum number of nodes and increase the maximum number of nodes to the following values:
• Minimum nodes: 0
• Maximum nodes: 8
You need to reconfigure the compute resource.
What are three possible ways to achieve this goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Data Preparation and Processing
Deployment and Monitoring
You configure a Deep Learning Virtual Machine for Windows.
You need to recommend tools and frameworks to perform the following:
• Build deep neural network (DNN) models
• Perform interactive data exploration and visualization
Which tools and frameworks should you recommend? To answer, drag the appropriate tools to the correct tasks. Each tool may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
You need to recommend tools and frameworks to perform the following:
• Build deep neural network (DNN) models
• Perform interactive data exploration and visualization
Which tools and frameworks should you recommend? To answer, drag the appropriate tools to the correct tasks. Each tool may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Data Preparation and Processing
Modeling
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