(Image by Laughing Squid)
Yesterday I read a paper by Tom Mitchell, the chair of the Machine Learning Department at Carnegie Mellon University, about the field of Machine Learning. This very readable introductory paper (a 7 page PDF document) can be found here. As stated by Dr. Mitchell, “Machine Learning seeks to answer the question ‘How can we build computer systems that automatically improve with experience, and what are the fundamental laws that govern all learning processes.’” The article surveys areas such as the current application successes of Machine Learning, active research questions, and ethical considerations in the discipline. If you’re at all interested in interdisciplinary computer goodness, I highly suggest checking it out.
Part of what I love about the idea of Machine Learning is that it unavoidably collides computer science, statistics, philosophy, psychology, neuroscience, and related learning fields. Researchers in this area are actively exploring the overlap (which is sometimes messy, no doubt) of various disciplines, following the trail of questions. I plan on writing more about this later. Good stuff. Check it out.