Linear Regression vs. Logistic Regression

I am writing this article to make a deep understanding of the similarity and differences between Linear and Logistic regression algorithm and their working with help of their code. As we know that Linear Regression is a supervised Machine Learning algorithm, is a statistical method which is used to study of relationships between two continuous variables i.e. dependent and independent variable. It also predicts continuous values and finds the best fitting line that describes variables. Logistic Regression is used to predict categorical data. It is an another supervised machine learning algorithm used statistically analyzing a dataset in which there are one or more independent variables that determine an outcome.