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NEW QUESTION: 1
A company deploys Microsoft Azure AD. You enable multi-factor authentication.
You need to inform users about the multi-factor authentication methods that they can use.
Which of the following methods is NOT a valid multi-factor authentication method in Microsoft 365?
A. Insert a small card in to a desktop computer and provide a PIN code when prompted
B. Receive an SMS text message that includes a verification code
C. Receive a call on a mobile phone and select the pound sign (#) when prompted
D. Receive an automated call on the desk phone that includes a verification code
Answer: A
Explanation:
Explanation
References:
http://techgenix.com/multifactor-authentication-office-365/

NEW QUESTION: 2
Click the calculator icon in the upper left-hand corner.
A clone source LUN is 2 TB in size. It performs 450 random 16 kB IOPs with a 2:1 R/W ratio. As part of ongoing testing, the clone is fractured for five minutes and then resynchronized. The testing is performed every hour.
How much data (to the nearest GB) is read from the source LUN as part of the resynchronization process?
A. 6 GB
B. 44 GB
C. 22 GB
D. 88 GB
Answer: B

NEW QUESTION: 3
Which choice below is NOT a common result of a risk analysis?
A. Adetailed listing of relevant threats
B. Definition of business recovery roles
C. Likelihood of a potential threat
D. Valuations of critical assets
Answer: B
Explanation:
The correct answer is "Definition of business recovery roles". The first three answers are common results of a risk analysis to determine the probability and effect of threats to company assets. Answer "Definition of business recovery roles"is a distracter.

NEW QUESTION: 4
You are developing a linear regression model in Azure Machine Learning Studio. You run an experiment to compare different algorithms.
The following image displays the results dataset output:

Use the drop-down menus to select the answer choice that answers each question based on the information presented in the image.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: Boosted Decision Tree Regression
Mean absolute error (MAE) measures how close the predictions are to the actual outcomes; thus, a lower score is better.
Box 2:
Online Gradient Descent: If you want the algorithm to find the best parameters for you, set Create trainer mode option to Parameter Range. You can then specify multiple values for the algorithm to try.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/evaluate-model
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regression