Anomaly detection is the process of identifying unexpected items or events in data sets. It’s about detecting the deviation from expected pattern of a dataset. It’s like having “spidey senses” for your apps that can detect when there’s danger or something is not right. Attend this session and learn about using anomaly detection in ML.NET, Azure Stream Analytics and Cognitive Services API, become a superhero and save the day.
Open in VS Code with Remote Containers
Use project mlnet\TempHumidityAnomalyDetection.csproj
It should build the dev container
Open in VS Code with Azure Stream Analytics Tools Installed
Use this workspace spideySenseASAProj\spideySenseASA.code-workspace
Follow instructions on this tutorial
Open browser to Raspberry PI Azure IoT Online Simulator
- copy and paste rpi-node every5sec.js to code window
- replace connectionString
Define Transformation Query using spideySenseASAProj.asaql instead of this query
Define live input and live output
Click on the link to run in binder
