This tutorial was presented as a Jupyter notebook during a workshop at the University of Minnesota. You can view it here.

This tutorial covers the basics of training and evaulating a linear regression model, using both text and non-text features. We will cover the bag-of-words representation, building a vocabulary based on word frequency, and examining the weights learned by our model.