The Discipline of Machine Learning

Tom Mitchell is one of the key personalities of Machine Learning discipline. He has been working in this area since the end of the 70's, published some reference ML textbooks and, first of all, he is the head of the first Machine Learning department all around the world.

In 2006, when he was "fighting" for the creation of the ML department at the Carnegie Mellon University, he was said that "you can only have a department if you have a discipline that is going to be here in one hundred years otherwise you can not have a department". For stating that ML would last more that a hundred years, he wrote a white paper, "The Discipline of Machine Learning", that is a real must-read paper for all the people interested in ML. The abstract of the paper states

Over the past 50 years the study of Machine Learning has grown from the efforts of a handful of computer engineers exploring whether computers could learn to play games, and a field of Statistics that largely ignored computational considerations, to a broad discipline that has produced fundamental statistical-computational theories of learning processes, has designed learning algorithms that are routinely used in commercial systems for speech recognition, computer vision, and a variety of other tasks, and has spun off an industry in data mining to discover hidden regularities in the growing volumes of online data. This document provides a brief and personal view of the discipline that has emerged as Machine Learning, the fundamental questions it addresses, its relationship to other sciences and society, and where it might be headed.

Tom also gave a speech related to this matter at the Carnegie Mellon University School of Computer Science's Machine Learning Department in March 2007. You can watch Mitchell's speech in this video.