In this tutorial, we will learn about binary logistic regression and its application to real life data using Python. We have also covered binary logistic regression in R in another tutorial. Without a doubt, binary logistic regression remains the most widely used predictive modeling method. Logistic Regression is a classification algorithm that is used to predict the probability of a categorical dependent variable. The method is used to model a binary variable that takes two possible values, typically coded as 0 and 1

## Multiple Linear Regression in R – a tutorial

Multiple Linear Regression (MLR) is the backbone of predictive modeling and machine learning and an in-depth knowledge of MLR is critical to understanding these key areas of data science. This tutorial is intended to provide an initial introduction to MLR using R. If you’d like to cover the same area using Python, you can find our tutorial here