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NEW QUESTION: 1
Your company uses Azure Sentinel.
A new security analyst reports that she cannot assign and dismiss incidents in Azure Sentinel. You need to resolve the issue for the analyst. The solution must use the principle of least privilege. Which role should you assign to the analyst?
A. Azure Sentinel Responder
B. Azure Sentinel Contributor
C. Azure Sentinel Reader
D. Logic App Contributor
Answer: A
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/sentinel/roles

NEW QUESTION: 2
Wie bezeichnen Sie einen Arbeitnehmer als Teilzeitbeschäftigten?
Bitte wählen Sie die richtige Antwort.
Hinweis: Die Antworten auf diese Frage werden von unseren Experten nicht überprüft Wählen Sie die entsprechenden Antworten aus.
A. Abwesenheiten so konfigurieren, dass die Uhrzeit verwendet wird
B. Cap.util.M (Kapazitätsauslastung) auf Infotyp IT0008 aktualisieren
C. Ändern Sie die vorhandene Arbeitszeitplanregel für Vollzeitbeschäftigte
D. Konfigurieren Sie Anwesenheiten so, dass die Uhrzeit verwendet wird
Answer: B

NEW QUESTION: 3
You are evaluating a Python NumPy array that contains six data points defined as follows:
data = [10, 20, 30, 40, 50, 60]
You must generate the following output by using the k-fold algorithm implantation in the Python Scikit-learn machine learning library:
train: [10 40 50 60], test: [20 30]
train: [20 30 40 60], test: [10 50]
train: [10 20 30 50], test: [40 60]
You need to implement a cross-validation to generate the output.
How should you complete the code segment? To answer, select the appropriate code segment in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Box 1: k-fold
Box 2: 3
K-Folds cross-validator provides train/test indices to split data in train/test sets. Split dataset into k consecutive folds (without shuffling by default).
The parameter n_splits ( int, default=3) is the number of folds. Must be at least 2.
Box 3: data
Example: Example:
>>>
>>> from sklearn.model_selection import KFold
>>> X = np.array([[1, 2], [3, 4], [1, 2], [3, 4]])
>>> y = np.array([1, 2, 3, 4])
>>> kf = KFold(n_splits=2)
>>> kf.get_n_splits(X)
2
>>> print(kf)
KFold(n_splits=2, random_state=None, shuffle=False)
>>> for train_index, test_index in kf.split(X):
print("TRAIN:", train_index, "TEST:", test_index)
X_train, X_test = X[train_index], X[test_index]
y_train, y_test = y[train_index], y[test_index]
TRAIN: [2 3] TEST: [0 1]
TRAIN: [0 1] TEST: [2 3]
References:
https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html

NEW QUESTION: 4
What features does Cisco FTDv provide over ASAv?
A. Cisco FTDv supports URL filtering while ASAv does not
B. Cisco FTDv runs on VMWare while ASAv does not
C. Cisco FTDv runs on AWS while ASAv does not
D. Cisco FTDv provides 1GB of firewall throughput while Cisco ASAv does not
Answer: A