In this lesson, we'll introduce 5 very effective machine learning algorithms for regression tasks. They each have classification counterparts as well.
And yes, just 5 for now. Instead of giving you a long list of algorithms, our goal is to explain a few essential concepts (e.g. regularization, ensembling, automatic feature selection) that will teach you why some algorithms tend to perform better than others.
In applied machine learning, individual algorithms should be swapped in and out depending on which performs best for the problem and the dataset. Therefore, we will focus on intuition and practical benefits over math and theory.