In this lesson, we're going to take a break from coding to learn a little bit more about regression problems and the five machine learning algorithms that are often used to solve them. You're also going to learn a lot about overfitting and the tools at your disposal to prevent it. By the end of the lesson, you'll be familiar with the characteristics of regression problems, overfitting, regularized regression models, including the lasso model ridge and elastic net models, as well as decision tree ensemble models, including the random forest and gradient boosting models, which are super powerful machine learning models that you're going to use all the time in practice.