Following up on my last article, “Demystifying machine learning,” it’s clear that the machine learning space has blossomed over the last few years. Machine learning technologies are gaining momentum and application in the enterprise. Competition is fierce with many new companies entering the market, and, it is not surprising that this has led to some confusion and doubt in the market, particularly as new entrants try to find their way—and their voice—in a world of competing visions.
As a result, there is much debate about which technology and methodology is best and, specifically in the field of machine learning, which methods are the right ones to use for a task. Each vendor will undoubtedly have a perspective to bring to the table and, of course, there is room for many differing approaches. However, what is not in dispute are the methods—what they are and what they should be used for.