All deep learning is statistical model building

Deep learning is often used to make predictions for data driven analysis. But what are the meanings of these predictions? This post explains how neural networks used in deep learning provide the parameters of a statistical model describing the probability of the occurrence of events. Data, observables, events or any other way of describing the things we can see and/or collect is absolute: we roll two sixes on a pair of six-sided dice or we get some other combination of outcomes; we toss a coin 10 times and we get heads each time or we get some other mixture of heads and tails; our universe evolves some way and we observe it, or it doesn't -- and we don't. We do not know, a priori, whether we will get two sixes with our dice roll or heads each time we toss a coin or what possible universes could exist for us to come into being and observe it.