Textbook in PDF format What are we “learning” in Machine Learning (ML)? This is a hard question to which we can only give a somewhat fuzzy answer. But at a high enough level of abstraction, there are two answers: algorithms, which solve some kinds of inference problems; models for datasets. These answers are so abstract that they are probably completely unsatisfying. But let’s (start to) clear things up, by looking at some particular examples of “inference" and “modeling" problems