Machine learning (ML) methodologies are booming in multiple application domains including spatial sciences. This momentum of popularity is largely driven by their superior predictive performances, especially for complex and noisy modelling challenges. In this session, I would like to outline the philosophy of ML with emphasis on the ensemble learning approach and walk through a case study to illustrate its application in geoscience.