70-774 · Question #46
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…
The correct answer is B. Azure Machine Learning Studio. 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…
Question
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?
Options
- Athe edX Data Science Learning Dashboard
- BAzure Machine Learning Studio
- CCortana Intelligence Gallery
- Dthe Data Science Virtual Machine
How the community answered
(47 responses)- A15% (7)
- B72% (34)
- C4% (2)
- D9% (4)
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. 4. Type a name and description for the new endpoint.
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