Bridging the Gap: From Analytical Models to Operational Success
Deploying machine learning models in production carries its own unique set of challenges. Some challenges stem from different, and sometimes conflicting, objectives between analytics and production. Others arise from technological limitations, business requirements, and even regulatory needs.
In this talk, we will focus on the part of the problem surrounding the handover of models from analytics to production. We expect data scientists, operation specialists, and product owners to benefit from our stories.