One of the technologies that Microsoft is promoting heavily is machine learning. This has rapidly gone from a technology that I heard little about to being in multiple keynotes that I’ve seen at large conferences this year. It almost seems that I can’t go a week without seeing some sort of machine learning article, announcement, or reference.
How applicable is machine learning for most of us? I’m not sure, but banks have certainly taken advantage of machine learning to reduce their risks associated with fraud and their systems work well. In fact, given the ways in which I travel, I’m amazed that I don’t get more calls about fraud related to my card use. With me in a new state almost every month, on a very irregular schedule, sometimes buying computer supplies far from home, I get called by a bank once or twice a year.
Across the ten or so calls I’ve gotten in the last few years, only one questioned legitimate purchases. The rest caught fraud on the same day that someone tried to use my card without my knowledge. That’s a very successful rate of both true positives, and a very, very low rate of false positives. I’m impressed.
If you haven’t played with machine learning, Microsoft has made it easy to give a try in Azure. You don’t even need to put in a credit card to get up and working with machine learning. Whether it’s applicable to your industry or not, you’ll have to decide, but I do think that lots of tedious analysis that humans do now could be better done by a machine.
At least after one of us humans has configured the algorithms and trained the machine to recognize patterns. And, of course, with one of us technologists periodically tuning the system to work better and monitoring the analysis as data changes.