Machine Learning, Aritificial Intelligence, Data Science, Programming, Deep Learning.
as: Such samples may be collected with interviews from random phone calls. But in ML, we may assume a condensed probability model p is already modeled and trained with expert knowledge and training data. Once the model is known, we can draw samples from this distribution p to make inferences.