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NEW QUESTION: 1
When implementing context-aware location services on the Cisco WCS through the MSE, which two types of data or functionality are only available after adding an MSE? (Choose two.)
A. ability to set email alerting options for rogue access points
B. ability to define WCS map boundaries
C. location of only one wireless client at a time on the WCS map
D. location of multiple wireless clients at a time on the WCS map
E. client location history
Answer: D,E
NEW QUESTION: 2
A company wants to allow users who belong to an account team to see all the Opportunities associated with that Account in Einstein Analytics.
Which two actions accomplish this requirement? Choose 2 answers
A. In the dataflow, extract the AccountTeamMember object and augment it with the Opportunity object using 'Accountld' as the join field and apply following security predicate: 'AccountTeamMember.Userld' == "$User.Id".
B. In the dataflow, extract the OpportunityTeamMember object and augment it with the Opportunity object using 'Opportunityld' as the join field and apply the following security predicate: 'OpportunityTeamMember.Userld' == "$User.Id".
C. Apply sharing inheritance.
D. Create a master-detail relationship between the Salesforce Account and Opportunity objects.
Answer: A,C
NEW QUESTION: 3
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
Start of repeated scenario
You plan to create a predictive analytics solution for credit risk assessment and fraud prediction in Azure Machine Learning. The Machine Learning workspace for the solution will be shared with other users in your organization. You will add assets to projects and conduct experiments in the workspace.
The experiments will be used for training models that will be published to provide scoring from web services.
The experiment for fraud prediction will use Machine Learning modules and APIs to train the models and will predict probabilities in an Apache Hadoop ecosystem.
End of repeated scenario.
The users will use different data sources that follow a standard format. The users will receive results in a standard format by using the fraud prediction web service. The results will be saved to a location specified by the users.
You need to provide the users with the ability to get results for different risk tolerances without affecting the calculation of the model.
Which three modules should be configured to use the Web Service Parameters? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. Evaluate Model
B. Import Data
C. Time Series Anomaly Detection
D. Select Columns in Dataset
E. Export Data
Answer: A,B,E
Explanation:
Explanation/Reference:
Explanation:
A: From scenario: The experiment for fraud prediction will use Machine Learning modules and APIs to train the models and will predict probabilities in an Apache Hadoop ecosystem.
BD: An Azure Machine Learning web service is created by publishing an experiment that contains modules with configurable parameters. In some cases, you may want to change the module behavior while the web service is running. Web Service Parameters allow you to do this task.
A common example is setting up the Import Data module so that the user of the published web service can specify a different data source when the web service is accessed. Or configuring the Export Data module so that a different destination can be specified References: https://docs.microsoft.com/en-us/azure/machine-learning/studio/web-service-parameters