The aim of this article is to fit and interpret a Multiple Linear Regression and Binary Logistic Regression using Statsmodels python package similar to statistical programming language R.
Market Mix Modelling (MMM) is an analytical approach that turns marketing and sales data into a quantity that can measure the impact of the marketing channels on the sales volume.
Gradient descent is an optimization algorithm used to minimize a cost function (i.e. Error) parameterized by a model. We know that Gradient means the slope of a surface or a line. This algorithm involves calculations with slope.
How to implement multiple linear regression and interpret the results. Source code and interesting basketball player dataset has been provided.