Hands-On Data Science with R

Machine learning vocabulary

At the end of the last section, we already hypothesized why machine learning managed to diverge in vacabulary from statistcs. Let me begin this section by discussing why the core ideas converge in essence. Many statistical methods crave to prae e videre, that is Latin for to see something that did not happen yet before it actually does, or simply, predict.

Prediction tasks, as other pattern recognition duties, often require a very sharp ability to comprehend data and generalize well into yet unseen information. This sort of shared goal drove the distinct efforts from traditional statistics and machine learning to many common places. Also, statistics, virtue to conceive all sorts of events in a probabilistic way ...