To get a better understanding of linear regression, we want to build a simple model that can be applied to one of the most famous machine learning datasets: the Boston housing prices dataset. Here, the goal is to predict the value of homes in several Boston neighborhoods in the 1970s, using information such as crime rate, property tax rate, distance to employment centers, and highway accessibility.