There are a plethora of algorithms or mathematical recipes that produce a model (a machine that takes an input and produces an output), each with different strengths and weaknesses. To better understand those strengths and weaknesses, three buckets of batch supervised machine learning algorithms will be considered: Regressions, Ensembles, and Others.