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QUESTION 19
You plan to use Azure Machine Learning to develop a predictive model. You plan to include an Execute Python Script module.
What capability does the module provide?
A. Outputting a file to a network location.
B. Performing interactive debugging of a Python script.
C. Saving the results of a Python script run in a Machine Learning environment to a local file.
D. Visualizing univariate and multivariate summaries by using Python code.
Answer: D
Explanation:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/execute-python-scripts
QUESTION 20
You are building an Azure Machine Learning experiment.
You need to transform a string column into a label column for a Multiclass Decision Jungle module.
Which module should you use?
A. Select Columns Transform
B. Group Categorical Values
C. Convert to Indicator Values
D. Edit Metadata
Answer: D
QUESTION 21
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 sections, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are designing an Azure Machine Learning workflow.
You have a dataset that contains two million large digital photographs.
You plan to detect the presence of trees in the photographs.
You need to ensure that your model supports the following:
Hidden layers that support a directed graph structure
User-defined core components on the GPU
Solution: You create an endpoint to the Computer vision API.
Does this meet the goal?
A. Yes
B. No
Answer: B
QUESTION 22
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 sections, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are designing an Azure Machine Learning workflow.
You have a dataset that contains two million large digital photographs.
You plan to detect the presence of trees in the photographs.
You need to ensure that your model supports the following:
Hidden layers that support a directed graph structure
User-defined core components on the GPU
Solution: You create an Azure notebook that supports the Microsoft Cognitive Toolkit.
Does this meet the goal?
A. Yes
B. No
Answer: B
QUESTION 23
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 sections, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are designing an Azure Machine Learning workflow.
You have a dataset that contains two million large digital photographs.
You plan to detect the presence of trees in the photographs.
You need to ensure that your model supports the following:
Hidden layers that support a directed graph structure
User-defined core components on the GPU
Solution: You create a Machine Learning experiment that implements the Multiclass Neural Network module.
Does this meet the goal?
A. Yes
B. No
Answer: A
QUESTION 24
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 sections, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are designing an Azure Machine Learning workflow.
You have a dataset that contains two million large digital photographs.
You plan to detect the presence of trees in the photographs.
You need to ensure that your model supports the following:
Hidden layers that support a directed graph structure
User-defined core components on the GPU
Solution: You create a Machine Learning experiment that implements the Multiclass Decision Jungle module.
Does this meet the goal?
A. Yes
B. No
Answer: B
QUESTION 25
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 sections, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are working on an Azure Machine Learning experiment.
You have the dataset configured as shown in the following table.
You need to ensure that you can compare the performance of the models and add annotations to the results.
Solution: You consolidate the output of the Score Model modules by using the Add Rows module, and then use the Execute R Script module.
Does this meet the goal?
A. Yes
B. No
Answer: B
Explanation:
https://msdn.microsoft.com/en-us/library/azure/dn905915.aspx
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