Regression analysis is the starting point in data science. This is because regression models represent the most well-understood models in numerical simulation. Once we experience the workings of regression models, we will be able to understand all other machine learning algorithms. Regression models are easily interpretable as they are based on solid mathematical bases (such as matrix algebra, for example). In the following sections, we will see that linear regression allows us to derive a mathematical formula that's representative of the corresponding model. Perhaps this is why such techniques are extremely easy to understand.
Regression analysis is a statistical process that's implemented to study the relationship between a set of independent variables (explanatory variables) and the dependent variable (response variable). Through this...
