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NEW QUESTION: 1
You have a virtual network named VNet1 as shown in the exhibit.
No devices are connected to VNet1.
You plan to peer VNet1 to another virtual network named Vnet2 in the same region. VNet2 has an address space of 10.2.0.0/16.
You need to create the peering.
What should you do first?
A. Create a subnet on VNet1 and VNet2.
B. Configure a service endpoint on VNet2
C. Add a gateway subnet to VNet1.
D. Modify the address space of VNet1.
Answer: D
Explanation:
The virtual networks you peer must have non-overlapping IP address spaces.
References:
https://docs.microsoft.com/en-us/azure/virtual-network/virtual-network-manage- peering#requirements-and-constraints
NEW QUESTION: 2
Your company deploys an Office 365 tenant.
You need to ensure that you can view service health and maintenance reports for the past seven days.
What are two possible ways to achieve this goal? Each correct answer presents a complete solution.
A. View the service health current status page of the Office 365 admin center.
B. Subscribe to the Office 365 Service Health RSS Notifications feed.
C. View the service settings page of the Office 365 admin center.
D. Run the Microsoft Online Services Diagnostics and Logging (MOSDAL) Support Kit.
Answer: A,B
Explanation:
Explanation
You can log into Office 365 as an Office365Administrator and view the Service Health Page to view the status of your Office 365 services. You can use the Service Health Page to view information on the status of your services for the current day or you can select the previous 6 days or 30 days for a historical view.
The following icons are used in the Service Health Page:
* A plain green tick indicates that the service is available and there have been no incidents during the reported time period.
* A grey question mark in a circle indicates that a potential issue is currently under investigation.
* A plain green tick with a plus sign indicates that a reported issue was a false positive.
* A white down arrow in a red circle indicates that the service is offline.
* A white up arrow in an orange circle indicates that a service incident is currently being resolved.
* A white right-facing arrow in an orange circle indicates that the service is degraded.
* A white exclamation mark in a blue circle indicates that there was an incident during a previous day and that more information is displayed in the Today column.
* A white square indicates that a post incident report has been published.
In the top right corner of the Service Health page, there is an RSS icon. You can click on the RSS icon to sign up for the service health RSS feed, which will email you when a new event is added or an existing event is updated.
NEW QUESTION: 3
You are creating an experiment by using Azure Machine Learning Studio.
You must divide the data into four subsets for evaluation. There is a high degree of missing values in the dat a. You must prepare the data for analysis.
You need to select appropriate methods for producing the experiment.
Which three modules should you run in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
Answer:
Explanation:
Explanation:
The Clean Missing Data module in Azure Machine Learning Studio, to remove, replace, or infer missing values.
Incorrect Answers:
Latent Direchlet Transformation: Latent Dirichlet Allocation module in Azure Machine Learning Studio, to group otherwise unclassified text into a number of categories. Latent Dirichlet Allocation (LDA) is often used in natural language processing (NLP) to find texts that are similar. Another common term is topic modeling.
Build Counting Transform: Build Counting Transform module in Azure Machine Learning Studio, to analyze training data. From this data, the module builds a count table as well as a set of count-based features that can be used in a predictive model.
Missing Value Scrubber: The Missing Values Scrubber module is deprecated.
Feature hashing: Feature hashing is used for linguistics, and works by converting unique tokens into integers.
Replace discrete values: the Replace Discrete Values module in Azure Machine Learning Studio is used to generate a probability score that can be used to represent a discrete value. This score can be useful for understanding the information value of the discrete values.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data