  MLJ (Machine Learing in Julia) is an open source software package providing a
common interface for interacting with machine learning models written in Julia
and other languages. It provides tools and meta-algorithms for selecting,
tuning, evaluating, composing and comparing those models, with a focus on
flexible model composition. In this design overview we detail chief novelties
of the framework, together with the clear benefits of Julia over the dominant
multi-language alternatives.
