Linear regression

Finally! We will explore our first true machine learning model. Linear regression is a form of regression, which means that it is a machine learning model that attempts to find a relationship between predictors and a response variable, and that response variable is, you guessed it, continuous! This notion is synonymous with making a line of best fit.

In the case of linear regression, we will attempt to find a linear relationship between our predictors and our response variable. Formally, we wish to solve a formula of the following format:

Let's look at the constituents of this formula:

• y is our response variable
• x_i is our i^th variable (i^th column or i^th predictor)
• B₀ is the intercept
• B_i is the coefficient for the x_i term

Let's take a look at some data before we go in depth. This dataset is publically available and attempts to predict the number of bikes needed on a particular day for a bike sharing program:

# read the data and set the datetime as the index 
# taken from...