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DP-100 Exam Dumps - Designing and Implementing a Data Science Solution on Azure

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Question # 9

You need to select an environment that will meet the business and data requirements.

Which environment should you use?

A.

Azure HDInsight with Spark MLlib

B.

Azure Cognitive Services

C.

Azure Machine Learning Studio

D.

Microsoft Machine Learning Server

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Question # 10

You need to define a process for penalty event detection.

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.

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Question # 11

You need to implement a scaling strategy for the local penalty detection data.

Which normalization type should you use?

A.

Streaming

B.

Weight

C.

Batch

D.

Cosine

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Question # 12

You need to use the Python language to build a sampling strategy for the global penalty detection models.

How should you complete the code segment? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

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Question # 13

You need to define an evaluation strategy for the crowd sentiment models.

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.

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Question # 14

You need to identify the methods for dividing the data according, to the testing requirements.

Which properties should you select? To answer, select the appropriate option-, m the answer area. NOTE: Each correct selection is worth one point.

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Question # 15

You need to correct the model fit issue.

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.

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Question # 16

You need to implement a feature engineering strategy for the crowd sentiment local models.

What should you do?

A.

Apply an analysis of variance (ANOVA).

B.

Apply a Pearson correlation coefficient.

C.

Apply a Spearman correlation coefficient.

D.

Apply a linear discriminant analysis.

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