When I hear the word "ensemble", I think of two things: the grand canonical ensemble, and the brass ensemble. But today we're taking a look at ensemble learning, which is the canonical way that the grand top brass of data scientists augment and combine models. The need for ensembling arises when you're working at the cutting edge and a good model is not available. One model might anticipate a fraction of the cases, another a different fraction, and a third a different set again...