Simple linear regression is a statistical approach that allows us to study and summarize the relationship between two continuous quantitative variables. Simple linear regression is used in machine learning models, mathematics, statistical modeling, forecasting epidemics, and other quantitative fields. Out of the two variables, one variable is called the dependent variable, and the other variable is called the independent variable. Our goal is to predict the dependent variable's value based on the value of the independent variable. A simple linear regression aims to find the best relationship between X (independent variable) and Y (dependent variable).

This tutorial's code is available on Github and its full implementation as well on Google Colab. Simple linear regression is a statistical approach that allows us to study and summarize the relationship between two continuous quantitative variables. Simple linear regression is used in machine learning models, mathematics, statistical modeling, forecasting epidemics, and other quantitative fields. Out of the two variables, one variable is called the dependent variable, and the other variable is called the independent variable. Our goal is to predict the dependent variable's value based on the value of the independent variable.

No one saw the crisis coming: a coordinated vandalistic effort to insert Squidward references into articles totally unrelated to Squidward. In 2006, Wikipedia was really starting to get going, and really couldn't afford to have any SpongeBob SquarePants-related high jinks sullying the site's growing reputation. Someone had to stop Squidward. The Wikipedia community knew it couldn't possibly mobilize human editors to face down the trolls--the onslaught was too great, the work too tedious. So instead an admin cobbled together a bot that automatically flagged errant insertions of the Cephalopod Who Shall Not Be Named.