Now that we’ve covered the basics of how to program and some of the data structures in Python, let’s switch our focus back to the theoretical and conceptual concepts of machine learning (ML) that were touched upon in the first chapter. This time around, we’ll start talking about specifics for each of these algorithms, namely, focusing on what their inputs and outputs are and how they work (at a high level; going any lower than that involves a fair amount of math that isn’t worth discussing in an introductory book).