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NEW QUESTION: 1
Ihre Firma hat 10 Büros.
Das Netzwerk enthält eine Active Directory-Domäne mit dem Namen contoso.com. Die Domäne enthält 500 Clientcomputer. Jedes Büro ist als separates Subnetz konfiguriert.
Sie stellen fest, dass eines der Büros Folgendes hat:
* Computer mit mehreren vorinstallierten Anwendungen
* Computer, die nicht standardmäßige Computernamen verwenden
* Computer, auf denen Windows 10 vorinstalliert ist
* Computer, die sich in einer Arbeitsgruppe befinden
Sie müssen die Computer so konfigurieren, dass sie die folgenden Unternehmensanforderungen erfüllen:
* Alle Computer müssen der Domäne angehören.
* Alle Computer müssen Computernamen haben, die das Präfix CONTOSO verwenden.
* Auf allen Computern müssen nur genehmigte Unternehmensanwendungen installiert sein.
Sie müssen eine Lösung zum erneuten Bereitstellen der Computer empfehlen. Die Lösung muss die Bereitstellungszeit minimieren.
A. Ein Bereitstellungspaket
B. Ein direktes Upgrade
C. Wischen und Laden aktualisieren
D. Windows-Autopilot
Answer: A
Explanation:
Explanation
By using a Provisioning, IT administrators can create a self-contained package that contains all of the configuration, settings, and apps that need to be applied to a device.

NEW QUESTION: 2

A. Option A
B. Option E
C. Option D
D. Option C
E. Option B
Answer: A,B

NEW QUESTION: 3
You are using C-Support Vector classification to do a multi-class classification with an unbalanced training dataset. The C-Support Vector classification using Python code shown below:

You need to evaluate the C-Support Vector classification code.
Which evaluation statement should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: Automatically adjust weights inversely proportional to class frequencies in the input data The "balanced" mode uses the values of y to automatically adjust weights inversely proportional to class frequencies in the input data as n_samples / (n_classes * np.bincount(y)).
Box 2: Penalty parameter
Parameter: C : float, optional (default=1.0)
Penalty parameter C of the error term.
References:
https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html