ai-toolkit-iot-edge/Predictive maintenance

IoT Scenario: General Predictive Maintenance

This scenario uses relatively large-scale data to walk the user through the main steps of an IoT AI project -- from data ingestion, feature engineering, model building, and then finally model operationalization and deployment. The code for the entire process is written in PySpark and implemented using Jupyter notebooks within Azure ML Workbench. The included Docker container can be deployed directly to an IoT device using Azure IoT Hub.

The detailed documentation for this real world scenario includes the step-by-step walk-through: https://docs.microsoft.com/azure/machine-learning/preview/scenario-predictive-maintenance

The public GitHub repository for this real world scenario contains all the code samples: https://github.com/Azure/MachineLearningSamples-PredictiveMaintenance