With greater understanding or appreciation for ML and AI, it’s easier to dispel the myths that may leave doubt about their full potential and to responsibly apply these productive solutions. A Tableau blog post recently explored three common machine learning misconceptions—reviewing them will help you discern fact from fiction in all the industry noise.
For anyone ready to embrace these models and put them to work, Andrew Beers, CTO at Tableau Software, wrote about how to effectively and responsibly apply AI techniques taking cues from brands such as Box, eBay, OpenTable, and Slack. And the rise of explainable AI (i.e. techniques in AI which can be trusted and easily understood) topped Tableau’s 2019 annual report of influential BI trends, signaling that more organizations are putting these trained, data-driven models to use in how they operate and solve complex challenges.