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NEW QUESTION: 1
Given:

A. e, e
o, o
B. e, e
i, o
C. a, e
i, o
D. a, e
o, o
Answer: D

NEW QUESTION: 2
Ein Unternehmen verwendet Power BI zum Erstellen von Visualisierungen.
Das IT-Support-Team des Unternehmens muss wissen, wann Power BI Desktop auf den Computern der Benutzer installiert werden muss und wo der Power BI-Dienst ausreicht, um Aufgaben auszuführen.
Sie müssen Lösungen für das Unternehmen empfehlen.
Was solltest du empfehlen? Um zu antworten, ziehen Sie die entsprechenden Komponenten auf die richtigen Anforderungen. Jede Komponente kann einmal, mehrmals oder gar nicht verwendet werden. Möglicherweise müssen Sie die geteilte Leiste zwischen den Fenstern ziehen oder einen Bildlauf durchführen, um den Inhalt anzuzeigen.
HINWEIS: Jede richtige Auswahl ist einen Punkt wert.

Answer:
Explanation:

Explanation

In a Venn diagram comparing Power BI Desktop and the Power BI service, the area in the middle shows how the two overlap. Some tasks you can do in either Power BI Desktop or the service. The two sides of the Venn diagram show the features that are unique to the application and the service.

Reference:
https://docs.microsoft.com/en-us/power-bi/designer/service-service-vs-desktop

NEW QUESTION: 3
トレーニングと検証のエラー値に大きな差があるモデルがあります。
新しいモデルを作成し、相互検証を実行する必要があります。
Azure Machine Learning Studioを使用して、新しいモデルのパラメーターセットを識別する必要があります。
各ステップで使用するモジュールはどれですか？答えるには、適切なモジュールを正しい手順にドラッグします。
各モジュールは、1回または複数回使用することも、まったく使用しないこともできます。コンテンツを表示するには、ペイン間で分割バーをドラッグするか、スクロールする必要がある場合があります。
注：それぞれの正しい選択には1ポイントの価値があります。

Answer:
Explanation:

Explanation:
Box 1: Split data
Box 2: Partition and Sample
Box 3: Two-Class Boosted Decision Tree
Box 4: Tune Model Hyperparameters
Integrated train and tune: You configure a set of parameters to use, and then let the module iterate over multiple combinations, measuring accuracy until it finds a "best" model. With most learner modules, you can choose which parameters should be changed during the training process, and which should remain fixed.
We recommend that you use Cross-Validate Model to establish the goodness of the model given the specified parameters. Use Tune Model Hyperparameters to identify the optimal parameters.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/partition-and-sample

NEW QUESTION: 4
A project team member tells you that she went to her project manager with a good idea for a useful change to the project. Instead of giving her approval to make the change, the project manager asked her to write a report describing the benefits of the change. What is the MOST appropriate advice for the situation?
A. The team member should do what was asked because this sort of information must be given to the project sponsor to make the change.
B. The project manager is being unreasonable and should do that kind of work herself.
C. Remind the project manager that the benefit cost analysis for the project was done during project planning.
D. A project manager must be able to weigh the benefits of the change versus the costs and compare them to other possible changes. The team member should do what was asked.
Answer: D