DP-100 Exam Questions
DP-100 Exam Info
Exam Name: Designing and Implementing a Data Science Solution on Azure
Exam Duration: 120 mins
Exam Format: Multiple Choice
Exam Type: Cloud Computing
Questions in Exam: 40-60 Questions
Exam Fee: $165 USD*
Language: English, Japanese, Chinese, Korean
Pass Score: 700 (on a scale of 1-1000)
Microsoft DP-100 Exam
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DP-100 Practice Questions
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Designing and Implementing a Data Science Solution on Azure Questions and Answers
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.
You need to implement a scaling strategy for the local penalty detection data.
Which normalization type should you use?
Post batch normalization statistics (PBN) is the Microsoft Cognitive Toolkit (CNTK) version of how to evaluate the population mean and variance of Batch Normalization which could be used in inference Original Paper.
In CNTK, custom networks are defined using the BrainScriptNetworkBuilder and described in the CNTK network description language "BrainScript."
Local penalty detection models must be written by using BrainScript.
You need to implement a feature engineering strategy for the crowd sentiment local models.
What should you do?
The linear discriminant analysis method works only on continuous variables, not categorical or ordinal variables.
Linear discriminant analysis is similar to analysis of variance (ANOVA) in that it works by comparing the means of the variables.
Data scientists must build notebooks in a local environment using automatic feature engineering and model building in machine learning pipelines.
Experiments for local crowd sentiment models must combine local penalty detection data.
All shared features for local models are continuous variables.
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