How to solve Machine Learning problems for production? (Part 2)
Machine Learning in industrial settings operates in a different context than in academia. To increase success, one must deviate from the original Waterfall-like method of conducting modelling and adopt a more flexible approach. This is what we describe as “Lean in ML”.