# SECTION 2
* you need to split the training set and a test set to balance the machine learning (you train on the test set and test those assumptions on the test set)
? what is categorical data, why whould you use it?

* feature scaling: put all values on the same scale so the larger number do not destroy other numbers => standardisation ou normalisation  

# Linear regression

Formula: `y = b0 + b1*x1`

y is the dependent variable. What is the value that changes in our model, the part that we want to understand from the work. How is this value changing. 

x is the independant variable, the one that has an implied association with y.

b1 is the coef for the independant variable, how a unit change in x1. 