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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. Azure Machine Learning Studio
C. the Data Science Virtual Machine
D. Cortana Intelligence Gallery
Answer: B
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
A customer is using a c3000 enclosure and wants to install a redundant Onboard Administrator (OA). What should the customer change in the existing enclosure to support the additional OA?
A. power supplies
B. OA rail kit
C. enclosure midplane
D. OA firmware
Answer: D

NEW QUESTION: 3
Azure Stream Analyticsジョブを使用してAzure IoTハブからのデータを処理するAIソリューションを設計します。 IoTハブは、工場で数千のIoTデバイスから時系列データを受信します。
ジョブは毎秒数百万のメッセージを出力します。さまざまなアプリケーションが利用可能なメッセージを消費します。メッセージをパージする必要があります。
ジョブの出力タイプを選択する必要があります。
目標を達成するための最適な出力タイプは何ですか？複数の回答を選択することで目標を達成できます。
A. Azure SQL Database
B. Azure Cosmos DB
C. Azure Blob storage
D. Azure Event Hubs
Answer: B
Explanation:
Stream Analyticsは、JSON出力用にAzure Cosmos DBをターゲットにできるため、非構造化JSONデータでのデータアーカイブと低遅延クエリを実現できます。
参照：
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-documentdb-output

NEW QUESTION: 4
An organization plans to use defined journal names for each purpose. They want to ensure that journal processing is easier and more secure.
The organization has the following requirements:
* Set up restrictions on the account type and segment values.
* Capture data accurately for offset accounts, currency, and financial dimensions.
* Maintain internal control and establish materiality limits.
You need to set up journal name elements to meet these requirements.
Which three journal elements should you configure? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. journal type
B. journal control
C. default values
D. workflow approval
E. account type
Answer: B,C,D

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