A Scalable End-to-End Anomaly Detection System using Azure Batch AI

This post is authored by Said Bleik, Senior Data Scientist at Microsoft. In a previous post I showed how Batch AI can be used to train many anomaly detection models in parallel for IoT scenarios. Although model training tasks are usually the most demanding ones in AI applications, making predictions at scale on a continuous… Read more

Training Many Anomaly Detection Models using Azure Batch AI

This post is authored by Said Bleik, Senior Data Scientist at Microsoft. In the IoT world, it’s not uncommon that you’d want to monitor thousands of devices across different sites to ensure normal behavior. Devices can be as small as microcontrollers or as big as aircraft engines and might have sensors attached to them to… Read more

Anomaly Detection – Using Machine Learning to Detect Abnormalities in Time Series Data

This post was co-authored by Vijay K Narayanan, Partner Director of Software Engineering at the Azure Machine Learning team at Microsoft. Introduction Anomaly Detection is the problem of finding patterns in data that do not conform to a model of “normal” behavior. Detecting such deviations from expected behavior in temporal data is important for ensuring… Read more