We have seen how to implement a linear regression algorithm in Python, and how to use the linear regression model from scikit-learn. We learned:
bvalue (intercept) and the
mvalue (slope) that minimize loss.
LinearRegression()model to perform linear regression on a set of points.
These are important tools to have in your toolkit as you continue your exploration of data science.
Try to perform linear regression on your own! If you find any cool linear correlations, make sure to share them!
As a starter, we’ve loaded in the Boston housing dataset. We made the
X values the nitrogen oxides concentration (parts per 10 million), and the
y values the housing prices. See if you can perform regression on these houses!