Machine Learning Pipeline Using Streaming IoT Sensor Data

Explore a practical machine learning pipeline using streaming IoT sensor data in this conference talk from Big Data Analytics Tokyo 2017. Learn how to process data from physical sensors using a distributed machine learning pipeline implemented with the H2O framework on the MapR Converged Data Platform. Follow a step-by-step demonstration of building a production-ready ML pipeline for real-time predictions, featuring live IoT sensors developed by a Tokyo-based startup. Gain insights into large-scale IoT machine learning applications suitable for engineers and data scientists with basic machine learning knowledge. Access the demo code and data to replicate the presented pipeline in your own projects.

Mathieu Dumoulin, MapR, Mateusz Dymczyk, H2O, Big Data Analytics Tokyo 2017