Come see some real, physical sensors generate data into a working distributed machine learning pipeline. We will demonstrate a working IoT large-scale ML pipeline implemented using the state of the art H2O framework on the MapR Converged Data Platform. We will begin the talk by using working, live IoT sensors made by a Tokyo-based startup. Then, we’ll take you step by step through the process of how we built a real, production ML pipeline that can make real-time predictions. This talk will be intermediate level and accessible to most engineers and data scientists with a minimal understanding of machine learning. We will also release our code and the data to replicate our demo publicly.