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arXiv · 2007.12285

MLJ: A Julia package for composable machine learning

Anthony D. Blaom·Franz Kiraly·Thibaut Lienart·Yiannis Simillides·Diego Arenas·Sebastian J. Vollmer
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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.

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Anthony D. Blaom, Franz Kiraly, Thibaut Lienart, Yiannis Simillides, Diego Arenas, Sebastian J. Vollmer. 2020-07-23. MLJ: A Julia package for composable machine learning. https://doi.org/10.21105/joss.02704

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