Machine learning and statistics with python

Introduction:                  picture credit to peter laurinec. I have been studying about PyGAM package for last couple of days. Now, I am planning to thoroughly analyze the code of PyGAM package with necessary description of GAM model and sources whenever necessary. This is going to be a long post and very much technical in nature. Pre-requisites: For understanding the coding part of PyGAM package, first you have to learn what is a GAM model. GAM stands for generalized additive model, i.e. it is a type of statistical modeling where a target variable Y is roughly represented by additive combination of set of different functions. In formula it can be written as: g(E[Y]) = f 1 (x 1 ) + f 2 (x 2 ) + f 3 (x 3 ,x 4 )+...etc where g is called a link function and f are different types of functions. In technical terms, in GAM model, theoretically expectation of the link transformed target variable is assume...