최신 DP-100 무료덤프 - Microsoft Designing and Implementing a Data Science Solution on Azure
You create an Azure Machine learning workspace.
You are use the Azure Machine -learning Python SDK v2 to define the search space for concrete hyperparafneters. The hyper parameters must consist of a list of predetermined, comma-separated.
You need to import the class from the azure ai ml. sweep package used to create the list of values.
Which class should you import?
You are use the Azure Machine -learning Python SDK v2 to define the search space for concrete hyperparafneters. The hyper parameters must consist of a list of predetermined, comma-separated.
You need to import the class from the azure ai ml. sweep package used to create the list of values.
Which class should you import?
정답: C
You are using Azure Machine Learning to monitor a trained and deployed model. You implement Event Grid to respond to Azure Machine Learning events.
Model performance has degraded due to model input data changes.
You need to trigger a remediation ML pipeline based on an Azure Machine Learning event.
Which event should you use?
Model performance has degraded due to model input data changes.
You need to trigger a remediation ML pipeline based on an Azure Machine Learning event.
Which event should you use?
정답: A
You manage an Azure Machine Learning workspace.
An MLflow model is already registered. You plan to customize how the deployment does inference. You need to deploy the MLflow model to a batch endpoint for batch inferencing. What should you create first?
An MLflow model is already registered. You plan to customize how the deployment does inference. You need to deploy the MLflow model to a batch endpoint for batch inferencing. What should you create first?
정답: A
You need to implement source control for scripts in an Azure Machine Learning workspace. You use a terminal window in the Azure Machine Learning Notebook tab You must authenticate your Git account with SSH.
You need to generate a new SSH key.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them m the correct order.
You need to generate a new SSH key.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them m the correct order.
정답:
Explanation:
You train a machine learning model.
You must deploy the model as a real-time inference service for testing. The service requires low CPU utilization and less than 48 MB of RAM. The compute target for the deployed service must initialize automatically while minimizing cost and administrative overhead.
Which compute target should you use?
You must deploy the model as a real-time inference service for testing. The service requires low CPU utilization and less than 48 MB of RAM. The compute target for the deployed service must initialize automatically while minimizing cost and administrative overhead.
Which compute target should you use?
정답: D
설명: (DumpTOP 회원만 볼 수 있음)
You use Azure Machine Learning to implement hyperparameter tuning with a Bandit early termination policy.
The policy uses a slack_factor set to 01. an evaluation interval set to 1, and an evaluation delay set to b.
You need to evaluate the outcome of the early termination policy
What should you evaluate? To answer, select the appropriate options m the answer area.
NOTE: Each correct selection is worth one point.
The policy uses a slack_factor set to 01. an evaluation interval set to 1, and an evaluation delay set to b.
You need to evaluate the outcome of the early termination policy
What should you evaluate? To answer, select the appropriate options m the answer area.
NOTE: Each correct selection is worth one point.
정답:
Explanation:
You load data from a notebook in an Azure Machine Learning workspace into a pandas dataframe named df.
The data contains 10.000 patient records. Each record includes the Age property for the corresponding patient.
You must identify the mean age value from the differentially private data generated by SmartNoise SDK.
You need to complete the Python code that will generate the mean age value from the differentially private data.
Which code segments should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
The data contains 10.000 patient records. Each record includes the Age property for the corresponding patient.
You must identify the mean age value from the differentially private data generated by SmartNoise SDK.
You need to complete the Python code that will generate the mean age value from the differentially private data.
Which code segments should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
정답:
Explanation:
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 creating a model to predict the price of a student's artwork depending on the following variables: the student's length of education, degree type, and art form.
You start by creating a linear regression model.
You need to evaluate the linear regression model.
Solution: Use the following metrics: Relative Squared Error, Coefficient of Determination, Accuracy, Precision, Recall, F1 score, and AUC.
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 creating a model to predict the price of a student's artwork depending on the following variables: the student's length of education, degree type, and art form.
You start by creating a linear regression model.
You need to evaluate the linear regression model.
Solution: Use the following metrics: Relative Squared Error, Coefficient of Determination, Accuracy, Precision, Recall, F1 score, and AUC.
Does the solution meet the goal?
정답: A
설명: (DumpTOP 회원만 볼 수 있음)
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?
정답: B
설명: (DumpTOP 회원만 볼 수 있음)
You have a Python script that executes a pipeline. The script includes the following code:
from azureml.core import Experiment
pipeline_run = Experiment(ws, 'pipeline_test').submit(pipeline)
You want to test the pipeline before deploying the script.
You need to display the pipeline run details written to the STDOUT output when the pipeline completes.
Which code segment should you add to the test script?
from azureml.core import Experiment
pipeline_run = Experiment(ws, 'pipeline_test').submit(pipeline)
You want to test the pipeline before deploying the script.
You need to display the pipeline run details written to the STDOUT output when the pipeline completes.
Which code segment should you add to the test script?
정답: B
설명: (DumpTOP 회원만 볼 수 있음)
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 analyzing a numerical dataset which contains missing values in several columns.
You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set.
You need to analyze a full dataset to include all values.
Solution: Calculate the column median value and use the median value as the replacement for any missing value in the column.
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 analyzing a numerical dataset which contains missing values in several columns.
You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set.
You need to analyze a full dataset to include all values.
Solution: Calculate the column median value and use the median value as the replacement for any missing value in the column.
Does the solution meet the goal?
정답: A
설명: (DumpTOP 회원만 볼 수 있음)
You use Azure Machine Learning to implement hyperparameter tuning for an Azure ML Python SDK v2- based model training.
Training runs must terminate when the primary metric is lowered by 25 percent or more compared to the best performing run.
You need to configure an early termination policy to terminate training jobs.
Which values should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Training runs must terminate when the primary metric is lowered by 25 percent or more compared to the best performing run.
You need to configure an early termination policy to terminate training jobs.
Which values should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
정답:
Explanation:
You create a pipeline in designer to train a model that predicts automobile prices.
Because of non-linear relationships in the data, the pipeline calculates the natural log (Ln) of the prices in the training data, trains a model to predict this natural log of price value, and then calculates the exponential of the scored label to get the predicted price.
The training pipeline is shown in the exhibit. (Click the Training pipeline tab.) Training pipeline
You create a real-time inference pipeline from the training pipeline, as shown in the exhibit. (Click the Real- time pipeline tab.) Real-time pipeline
You need to modify the inference pipeline to ensure that the web service returns the exponential of the scored label as the predicted automobile price and that client applications are not required to include a price value in the input values.
Which three modifications must you make to the inference pipeline? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Because of non-linear relationships in the data, the pipeline calculates the natural log (Ln) of the prices in the training data, trains a model to predict this natural log of price value, and then calculates the exponential of the scored label to get the predicted price.
The training pipeline is shown in the exhibit. (Click the Training pipeline tab.) Training pipeline
You create a real-time inference pipeline from the training pipeline, as shown in the exhibit. (Click the Real- time pipeline tab.) Real-time pipeline
You need to modify the inference pipeline to ensure that the web service returns the exponential of the scored label as the predicted automobile price and that client applications are not required to include a price value in the input values.
Which three modifications must you make to the inference pipeline? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
정답: A,B,D
You create an Azure Machine Learning pipeline named pipeline 1 with two steps that contain Python scnpts.
Data processed by the first step is passed to the second step.
You must update the content of the downstream data source of pipeline 1 and run the pipeline again.
You need to ensure the new run of pipeline 1 fully processes the updated content.
Solution: Change the value of the compute.target parameter of the PythonScriptStep object in the two steps.
Does the solution meet the goal'
Data processed by the first step is passed to the second step.
You must update the content of the downstream data source of pipeline 1 and run the pipeline again.
You need to ensure the new run of pipeline 1 fully processes the updated content.
Solution: Change the value of the compute.target parameter of the PythonScriptStep object in the two steps.
Does the solution meet the goal'
정답: A
You are creating a binary classification by using a two-class logistic regression model.
You need to evaluate the model results for imbalance.
Which evaluation metric should you use?
You need to evaluate the model results for imbalance.
Which evaluation metric should you use?
정답: D
설명: (DumpTOP 회원만 볼 수 있음)
You use an Azure Machine Learning workspace. Azure Data Factor/ pipeline, and a dataset monitor that runs en a schedule to detect data drift.
You need to Implement an automated workflow to trigger when the dataset monitor detects data drift and launch the Azure Data Factory pipeline to update the dataset. The solution must minimize the effort to configure the workflow.
How should you configure the workflow? To answer select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You need to Implement an automated workflow to trigger when the dataset monitor detects data drift and launch the Azure Data Factory pipeline to update the dataset. The solution must minimize the effort to configure the workflow.
How should you configure the workflow? To answer select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
정답:
Explanation:
You define a datastore named ml-data for an Azure Storage blob container. In the container, you have a folder named train that contains a file named data.csv. You plan to use the file to train a model by using the Azure Machine Learning SDK.
You plan to train the model by using the Azure Machine Learning SDK to run an experiment on local compute.
You define a DataReference object by running the following code:
You need to load the training data.
Which code segment should you use?
You plan to train the model by using the Azure Machine Learning SDK to run an experiment on local compute.
You define a DataReference object by running the following code:
You need to load the training data.
Which code segment should you use?
정답: A
설명: (DumpTOP 회원만 볼 수 있음)
You use the following Python code in a notebook to deploy a model as a web service:
The deployment fails.
You need to use the Python SDK in the notebook to determine the events that occurred during service deployment an initialization.
Which code segment should you use?
The deployment fails.
You need to use the Python SDK in the notebook to determine the events that occurred during service deployment an initialization.
Which code segment should you use?
정답: D
You have a model with a large difference between the training and validation error values.
You must create a new model and perform cross-validation.
You need to identify a parameter set for the new model using Azure Machine Learning Studio.
Which module you should use for each step? To answer, drag the appropriate modules to the correct steps.
Each module may be used once or 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 must create a new model and perform cross-validation.
You need to identify a parameter set for the new model using Azure Machine Learning Studio.
Which module you should use for each step? To answer, drag the appropriate modules to the correct steps.
Each module may be used once or 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.
정답:
Explanation:
Box 1: Split data
Box 2: Partition and Sample
Box 3: Two-Class Boosted Decision Tree
Box 4: Tune Model Hyperparameters
Integrated train and tune: You configure a set of parameters to use, and then let the module iterate over multiple combinations, measuring accuracy until it finds a "best" model. With most learner modules, you can choose which parameters should be changed during the training process, and which should remain fixed.
We recommend that you use Cross-Validate Model to establish the goodness of the model given the specified parameters. Use Tune Model Hyperparameters to identify the optimal parameters.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/partition-and-sample