The 10 Commandments of AI & ML (P1)
Building an enterprise AI application is problematic. Scaling ML and getting user adoption is even more challenging. Here are the rules to follow. The big day is finally here! After months of squabbles, discussions, and fistfights, you have managed to get the budget allocated for evaluating machine learning. You have identified the right AutoML tool and are eager to get started on your first proof of concept. Where do you begin? This project’s success will determine the course of the digital transformation journey, production roll-out at other business units, and perhaps earn you a fancy new title! If you want to do ML the right way, you need to follow a set of commandments. In this two-part blog series, we’ll cover the ten rules. Here are the top 5 : Start with critical objectives for the project, and think about alignment with business goals. Identify top use cases, key performance…
