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NEW QUESTION: 1
Wählen Sie für jede der folgenden Aussagen Ja aus, wenn die Aussage wahr ist. Andernfalls wählen Sie Nein. HINWEIS: Jede richtige Auswahl ist einen Punkt wert.
Answer:
Explanation:
Explanation
Box 1: No
Not all Azure regions support availability zones.
Box 2: No
Regions that support availability zones support Linux virtual machines.
Box 3: Yes
Availability Zones is a high-availability offering that protects your applications and data from datacenter failures. Availability Zones are unique physical locations within an Azure region. Each zone is made up of one or more datacenters equipped with independent power, cooling, and networking. To ensure resiliency, there's a minimum of three separate zones in all enabled regions. The physical separation of Availability Zones within a region protects applications and data from datacenter failures. Zone-redundant services replicate your applications and data across Availability Zones to protect from single-points-of-failure. With Availability Zones, Azure offers industry best 99.99% VM uptime SLA.
References:
https://docs.microsoft.com/en-gb/azure/availability-zones/az-overview
NEW QUESTION: 2
You have a server named Server1 that runs Windows Server 2016.
You need to identify whether any inbound rules on Server1 require that users be authenticated before they can connect to the server.
Which cmdlet should you use?
A. Get-NetFirewallPortFilter
B. Get-NetFirewallAddressFilter
C. Get-NetIPSecRule
D. Get-NetFirewallProfile
E. Get-NetFirewallSetting
F. Get-NetFirewallRule
G. Get-NetFirewallApplicationFilter
Answer: F
Explanation:
Explanation: The complete cmdlet to perform the required action:-
NEW QUESTION: 3
You have a dataset created for multiclass classification tasks that contains a normalized numerical feature set with 10,000 data points and 150 features.
You use 75 percent of the data points for training and 25 percent for testing. You are using the scikit-learn machine learning library in Python. You use X to denote the feature set and Y to denote class labels.
You create the following Python data frames:
You need to apply the Principal Component Analysis (PCA) method to reduce the dimensionality of the feature set to 10 features in both training and testing sets.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: PCA(n_components = 10)
Need to reduce the dimensionality of the feature set to 10 features in both training and testing sets.
Example:
from sklearn.decomposition import PCA
pca = PCA(n_components=2) ;2 dimensions
principalComponents = pca.fit_transform(x)
Box 2: pca
fit_transform(X[, y])fits the model with X and apply the dimensionality reduction on X.
Box 3: transform(x_test)
transform(X) applies dimensionality reduction to X.
References:
https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html