Getting Machine Learning Projects from Idea to Execution

Machine learning might be the world’s most important general-purpose technology, but it’s notoriously difficult to launch. Outside of Big Tech and a handful of other leading companies, machine learning initiatives routinely fail to deploy, never realizing value. What’s missing? A specialized business practice suitable for wide adoption. This article presents a six-step practice for ushering machine learning projects from conception to deployment. This disciplined approach serves both sides: It empowers business professionals and it establishes a sorely needed strategic framework for data professionals.