After you answer a question, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have Azure IoT Edge devices that generate streaming data. On the devices, you need to detect anomalies in the data by using Azure Machine Learning models. Once an anomaly is detected, the devices must add information about the anomaly to the Azure IoT Hub stream. Solution: You expose a Machine Learning model as an Azure web service. Does this meet the goal? A. Yes B. No  Suggested Answer: B Instead use Azure Stream Analytics and REST API. Note. Available in both the cloud and Azure IoT Edge, Azure Stream Analytics offers built-in machine learning based anomaly detection capabilities that can be used to monitor the two most commonly occurring anomalies: temporary and persistent. Stream Analytics supports user-defined functions, via REST API, that call out to Azure Machine Learning endpoints. References: https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-machine-learning-anomaly-detection This question is in AI-100 Designing and Implementing an Azure AI Solution Exam For getting Microsoft Certified: Azure AI Engineer Associate Certificate Disclaimers: The website is not related to, affiliated with, endorsed or authorized by Microsoft. The website does not contain actual questions and answers from Microsoft's Certification Exams. Trademarks, certification & product names are used for reference only and belong to Microsoft.
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