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NEW QUESTION: 1
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
Start of repeated scenario
You plan to use Azure platform tools to detect and analyze food items in smart refrigerators. To provide families with an integrated experience for grocery shopping and cooking, the refrigerators will connect to other smart appliances, such as stoves and microwave ovens, on a LAN.
You plan to build an object recognition model by using the Microsoft Cognitive Toolkit. The object recognition model will receive input from the connected devices and send results to applications.
The training data will be derived from more than 10 TB of images. You will convert the raw images to the sparse format.
End of repeated scenario.
You need to ensure that a web service endpoint can receive image data and use an object recognition model to return the expected object and the confidence level of the model.
The solution must minimize the effort required to generate the client code to access the web service.
Which resource should you use?
A. the edX Data Science Learning Dashboard
B. the Data Science Virtual Machine
C. Cortana Intelligence Gallery
D. Azure Machine Learning Studio
Answer: D
Explanation:
Explanation/Reference:
Explanation:
There are two ways to add an endpoint to a Web service.
Programmatically

Through the Azure Machine Learning Web Services portal

Adding an endpoint using the Azure Machine Learning Web Services portal
1. In Machine Learning Studio, on the left navigation column, click Web Services.
2. At the bottom of the Web service dashboard, click Manage endpoints. The Azure Machine Learning Web Services portal opens to the endpoints page for the Web service.
3. Click New.
4. Type a name and description for the new endpoint.
Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio/create-endpoint

NEW QUESTION: 2
SAP Fioriデザインの特徴は次のうちどれですか。
この質問には3つの正解があります。
応答：
A. ビジュアルデザイン
B. 相互作用パターン
C. 統一されたユーザーインターフェイス設計
D. デザイン思考の方法論
E. 情報アーキテクチャ
Answer: A,B,E

NEW QUESTION: 3
Refer to the exhibit.


A network administrator receives a call from a contractor that was recently given wireless access to the network. The user reports that the response time is slow and suggests there might be a problem with the WLAN. The network administrator checks RF performance in AirWave to find the user and sees the output shown in the exhibit.
What can the network administrator conclude after analyzing the data?
A. Client health is low, which suggests that there are packet drops and collisions in the RF environment.
B. Goodput is low in relation to connection speed, which suggests a channel with high utilization, another channel should be used.
C. Client health and CNR are high, therefore, it is unlikely the client is experiencing an RF-related issue.
D. Client health and SNR are high but usage is low; therefore, there might be packet drops.
Answer: B

NEW QUESTION: 4
An engineer must ensure that all client operating systems have the AnyConnect Agent for an upcoming posture implementation. Which two versions of OS does the AnyConnect posture agent support? (Choose two.)
A. Apple Mac OS X
B. Microsoft Windows
C. Red Hat Enterprise Linux
D. Google Android
E. Ubuntu
Answer: A