Last week we discussed what makes artificial intelligence…artificial intelligence. Over the past several years AI has grown increasingly popular, helped along by the mystique of its name. AI is one technique of many in the world of predictive analytics, though. While last week we talked about what artificial intelligence is, we didn’t go into as much detail about how it works.
Each week at CompassRed, we take a few minutes to share what we've been reading with you. Some of it's technical, some of it's topical, all of it's interesting.
by Dr. Steve Poulin
Over the past several years, artificial intelligence (AI) has received an increasing amount of attention (and scrutiny) recently because of the exciting new ways it is being used. Many people are familiar with the technologies that AI has enabled, but how many people actually know how it works? In this post, we'll explore what makes artificial intelligence...artificial intelligence.
by Dr. Steve Poulin
Those who are working with Predictive Analytics are always trying to find a better more effective way. We have chosen a field that that can get better and better every day. And in the last few years, with the development of new technologies and approaches to acquiring data – we are finding the spotlight on us to do just that: find better ways. Traditionally, there are three primary ways to develop models and algorithms for predictive analytics: (1) the expensive SAS solution, (2) the cheaper but just as effective IBM SPSS, or (3) the open source “R”. We, at CompassRed, think there is a fourth: Leverage the best of all.
CompassRed Data Labs announces today that they have been approved to become a certified IBM Business Partner.
by Steve Poulin and Patrick Callahan
As a Data and Analytics company, we at CompassRed have seen the full cycle of leveraging data for insight with each phase of development being just as important as any other. Deployment is the part of the predictive analytics process that puts the predictions to work. Predictive analytics requires a very time-consuming process of data preparation and a very complex process of finding the best algorithms (also known as “modeling”) for producing predictions. However, all of this effort is for naught if the predictions are not used by an organization to meet their objectives, which typically means increasing revenue and decreasing costs