The ML models we are going to describe in this book are all parametric models: this means that a model can be described using a function, where the input and output are known (in the case of supervised learning, it is clear), and the aim is to change the model parameters so that, given a particular input, the model produces the expected output.
Given an input sample, 
, and the desired outcome, 
, an ML model is a parametric function, , where is the set of model parameters to change during the training in order to fit the data ...
