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NEW QUESTION: 1
Your company has offices in several cities and 100.000 users.
The network contains an Active Directory domain contoso.com.
You purchase Microsoft 365 and plan to deploy several Microsoft 365 services.
You are evaluating the implementation of pass-through authentication and seamless SSO. Azure AD Connect will NOT be in staging mode.
You need to identify the redundancy limits for the planned implementation.
What should you identify? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:
Explanation

Azure AD Connect can be active on only one server. You can install Azure AD Connect on another server for redundancy but the additional installation would need to be in Staging mode. An Azure AD connect installation in Staging mode is configured and ready to go but it needs to be manually switched to Active to perform directory synchronization.
Azure authentication agents can be installed on as many servers as you like.
Reference:
https://docs.microsoft.com/en-us/azure/active-directory/hybrid/how-to-connect-pta-quick-start

NEW QUESTION: 2
Your network contains an Active Directory domain named contoso.com. The domain contains a domain-based Distributed file System (DFS) namespace named Namespace1 that has access-based enumeration enabled.
Namespace1 has a folder named folder1. Folder1 has a target of \\Server1\Folder1.
The Permission for folder1 are configured as shown in the following table.

Access-based enumeration is disabled for the share of Folder1.
You need to ensure that both User1 and User2 can see Folder1 when they access \\Contoso.com\NameSpace1 What should you do?
A. Enable access-based enumeration for Folder1.
B. Disable access-based enumeration for Namespace1.
C. Deny User1 the read DFS permission to Folder1.
D. Assign User1 the read NTFS permission to folder1
Answer: D
Explanation:
Explanation
https://docs.microsoft.com/en-us/windows-server/storage/dfs-namespaces/using-inherited-permissions-with-acce

NEW QUESTION: 3
Which of the following are feature engineering techniques? (Select 2 answers)
A. Hidden feature layers
B. Crossed feature columns
C. Feature prioritization
D. Bucketization of a continuous feature
Answer: B,D
Explanation:
Selecting and crafting the right set of feature columns is key to learning an effective model. Bucketization is a process of dividing the entire range of a continuous feature into a set of consecutive bins/buckets, and then converting the original numerical feature into a bucket ID (as a categorical feature) depending on which bucket that value falls into. Using each base feature column separately may not be enough to explain the data. To learn the differences between different feature combinations, we can add crossed feature columns to the model.
Reference:
https://www.tensorflow.org/tutorials/wide#selecting_and_engineering_features_for_the_model