In this tutorial, we will give a basic overview of the Anomaly Detector service in Cognitive Services, and how it can help in multiple industries like IoT, DevOps, and digital businesses to find anomalies in a device or system. I will show you how to use low-code ways to easily build a machine learning solution to detect these anomalies in the Synapse studio and with SynapseML library. You will learn how to develop and leverage this capability.

Learn more about the Anomaly Detection in Synapse release here: https://aka.ms/mvadblog/synapse
Follow along on this workshop with this Github repo: https://aka.ms/mvadsynapse/repo
Join the Teams Channel to discuss more: https://aka.ms/adAdvisorsJoin

Who is this session for? Data scientists, Software Engineers, Sales, or anyone with a need for building an anomaly detection solution in Synapse

Why should you attend? You will learn how to detect anomalies in time series data within various industries, like energy or manufacturin. There are easy and low-code ways to develop in Synapse, and I will help you understand the rationale of Anomaly Detector, SynapseML library, and Synapse Analytics Big Data Platform. This session should help make you feel more comfortable with using the Anomaly Detector in your Synapse, Databricks, or another Spark environment.

Speaker: Louise Han, Program Manager for the Cognitive Services Anomaly Detector team at Microsoft | https://www.linkedin.com/in/jingru-han-2aa58415a/