posted 3 years ago
Yes, in their most raw form: empirical data (input), mathematics (largely statistics giving the algorithm/process used in "learning"), inference (output/estimate).

Essentially the philosophy is that the underlying process that determines an outcome that we wish to derive is unknown or very complex. By using empirical data and a certain amount of mathematical/statistical sophistication we can arrive at an estimate that is more accurate on average than a hard-coded (i.e. non-learning based) algorithm. In many cases, we do not know enough about the process to even write an algorithm to describe it adequately; instead, we "let the data speak for itself" in determining a mathematical relationship.