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NEW QUESTION: 1
You create a dashboard that displays the results of a customer satisfaction survey.
You need to embed a tweet from your company's Twitter feed into the dashboard.
What should you do?
A. Edit the report and import a visualization from the marketplace. Pin the visualization to the dashboard.
B. To the dashboard, add a tile that uses a web content source.
C. To the dashboard, add a tile that uses a PubNub content source.
D. Edit the report and import a visualization from a file. Pin the visualization to the dashboard.
Answer: B
Explanation:
Explanation/Reference:
References:
https://docs.microsoft.com/en-us/power-bi/service-dashboard-add-widget

NEW QUESTION: 2
2つ以上の組織が具体的で、秘密の情報を互いを除いた誰とでも共有することを防止するつもりの協定文書が呼ばれる:
A. an MOU.
B. an RFP.
C. an SLA.
D. an NDA.
Answer: D
Explanation:
References:
Kim Heldman, CompTIA Project+ Study Guide, 2nd Edition, Sybex, Indianapolis, 2017, p. 302

NEW QUESTION: 3
Click on the Exhibit Button to view the Formula Sheet. Under the Model Code, if a broker shouts "done" or "mine" at the very moment a dealer shouts "off":
A. The central bank should be consulted.
B. No deal is done.
C. The deal is done.
D. It should be resolved in consultation with senior management.
Answer: C

NEW QUESTION: 4
チームデータサイエンス環境の構築を計画しています。機械学習パイプラインのトレーニングモデルのデータのサイズは20 GBを超えます。
次の要件があります。
*モデルはCaffe2またはChainerフレームワークを使用して構築する必要があります。
*データサイエンティストは、接続されたネットワーク環境と切断されたネットワーク環境の両方で、データサイエンス環境を使用して機械学習パイプラインを構築し、個人用デバイスでモデルをトレーニングできなければなりません。
*個人用デバイスは、ネットワークに接続するときに機械学習パイプラインの更新をサポートする必要があります。
データサイエンス環境を選択する必要があります。
どの環境を使用する必要がありますか？
A. Azure Machine Learning Service
B. Azure Machine Learning Studio
C. Azure Kubernetes Service（AKS）
D. Azure Databricks
Answer: A
Explanation:
The Data Science Virtual Machine (DSVM) is a customized VM image on Microsoft's Azure cloud built specifically for doing data science. Caffe2 and Chainer are supported by DSVM.
DSVM integrates with Azure Machine Learning.
Incorrect Answers:
B: Use Machine Learning Studio when you want to experiment with machine learning models quickly and easily, and the built-in machine learning algorithms are sufficient for your solutions.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/overview