Abstract
Azure Stream Analytics is an event-processing engine that allows users to analyze high volumes of data streaming from devices, sensors, and applications. Azure Stream Analytics can be used for Internet of Things (IoT) real-time analytics, remote monitoring and data inventory controls. However, Azure Stream Analytics is another component in Azure on which we could run machine learning. It is possible to use a machine learning model API created in Azure ML Studio inside Azure Stream Analytics for applying machine learning to streaming data from sensors, applications, and live databases. In this chapter, I will explain how to use machine learning inside Azure Stream Analytics. First, a general introduction to Azure Stream Analytics is given, then, a simple example of an Azure ML Studio API that is going to be applied to the stream data is presented.
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© 2019 Leila Etaati
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Etaati, L. (2019). Machine Learning in Azure Stream Analytics. In: Machine Learning with Microsoft Technologies. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-3658-1_13
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DOI: https://doi.org/10.1007/978-1-4842-3658-1_13
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Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-3657-4
Online ISBN: 978-1-4842-3658-1
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