In the latest Developer Impact Series, Dave Neary of Ampere® Computing talks with Dr. R.J. Nowling from the Milwaukee School of Engineering to discuss how the school is bridging the gap between theoretical machine learning (ML) and real-world production systems and about how students learn to build “real” ML systems that work in everyday software — not just clever math models.Dr. Nowling explains that lots of schools teach students how to design smart computer models. MSOE tries to go one step further. The key idea is: a model isn’t helpful if it only works in a lab. In the real world, a working system also needs other parts — like getting fresh data, connecting to databases, turning raw information into the kind of numbers the model can use, and keeping track of whether the model is still doing well over time.