Evidence-driven disaster risk manage- ment relies upon many different data types, information sources, and types of models to be effective.Tasks such as weather modelling, earthquake fault line rupture, or the development of dynamic urban exposure measures involve complex science and large amounts of data from a range of sources.ML algorithms were pioneered in fields like satellite remote sensing and statistical data analysis.