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NEW QUESTION: 1
A. Option D
B. Option A
C. Option E
D. Option C
E. Option B
Answer: A,C,D
NEW QUESTION: 2
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. Azure Machine Learning Studio
B. Cortana Intelligence Gallery
C. the Data Science Virtual Machine
D. the edX Data Science Learning Dashboard
Answer: A
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: 3
When is it acceptable not to take action on an identified risk?
A. When the necessary countermeasure is too complex.
B. Never. Good security has to address and reduce all risks.
C. When political issues prevent this type of risk from being addressed.
D. When the cost of the countermeasure outweighs the value of the asset and the potential loss.
Answer: D
NEW QUESTION: 4
Refer to the exhibit. After you apply the given configuration to a router, the DHCP clients behind the device cannot communicate with hosts outside of their subnet. Which action is most likely to correct the problem?
A. Configure the DNS server on the same subnet as the clients.
B. Correct the subnet mask.
C. Configure the default gateway.
D. Activate the DHCP pool.
Answer: C
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