MLJ: A Julia package for composable Machine Learning

Anthony D. Blaom, Franz J. Király, Thibaut Liénart, Yiannis Simillides, Diego Arenas, Sebastian J. Vollmer

Abstract: 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.