Integrating machine learning in existing business processes

Why is it challenging to turn a data science use case into a successful data product? One of the challenges of embedding machine learning models in companies is that advanced data science solutions do not automatically match the existing business context. In this talk Sven Stringer will discuss an example use case to show what factors can cause a mismatch and - more importantly - how to solve it. A key ingredient to a successful data product is a carefully designed interface between a machine learning model and the humans involved in the existing business process. Implementing such an interface therefore requires technological solutions as well as changes on the process side. Concrete examples of both will guide you to successfully embed machine learning models in your own context.