Understanding regression
Regression is a form of supervised learning that involves training a model to predict a numerical value for a single label column for new rows the model hasn’t seen before.
Using a trained regression model, you can predict numerical values such as the following:
- Prices of services and commodities
- Durations of commutes
- Sports scores or point differentials
- Volumes of customers or sales
- Number of readers for a prospective blog post or book
Since being able to predict a number has so many uses, regression models can serve almost any industry – provided you have an adequate dataset to train your regression model.
Our regression task
In this chapter, we’ll be training and evaluating a regression model related to our football dataset. Specifically, we’ll attempt to calculate an expected salary for a footballer based on their current season and last season’s performance, their age, their position...
