In the previous chapter, we already gained some basic understanding of the machine learning (ML) process, as we have seen the basic distinction between regression and classification. Regression analysis is a set of statistical processes for estimating the relationships between a set of variables called a dependent variable and one or multiple independent variables. The values of dependent variables depend on the values of independent variables.
A regression analysis technique helps us to understand this dependency, that is, how the value of the dependent variable changes when any one of the independent variables is changed, while the other independent variables are held fixed. For example, let's assume that there will be more savings in someone's bank when they grow older. Here, the amount of Savings (say in million $) depends on age...