Linear regression is a statistical modeling technique. It utilizes a dependent variable, which can be discrete or continuous number and one independent variable. Linear regression models are simple to train by using machine learning. In many cases are the first type of machine learning models to try to train when using a new data set.
One example of a linear regression function is:
f(x)=y=a*x+b
The generalization of this function for ML models is performed by using linear algebra matrices.
