Handling Truth by Embedding ML into Databases

Machine learning helps organizations handle the truth by enabling them to create an accurate data model from among huge stores of data and then build processes that are constantly improving through input from the community. This is easier said than done, however, because today's ML tools ecosystem is incredibly complex, and organizations often don't have people with the skills to navigate it. In addition, organizations have a difficult time trusting the so-called black box output of many ML models. Go here to see a listing of eWEEK's Top Predictive Analytics Companies. This eWEEK Data Points article, using industry information from MarkLogic Senior Product Manager Anthony Roach, offers eight things you need to know about the current state of ML and how embedding ML into the database platform enables organizations to innovate quickly and intelligently, based on trusted data and trusted analysis of that data.