MLJ: A Julia package for composable machine learning

• URL: http://arxiv.org/abs/2007.12285v2
• Date: Tue, 3 Nov 2020 23:06:45 GMT
• Title: MLJ: A Julia package for composable machine learning
• Authors: Anthony D. Blaom, Franz Kiraly, Thibaut Lienart, Yiannis Simillides, Diego Arenas, Sebastian J. Vollmer
• Abstract summary: MLJ is an open source software package 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.
• Score: 0.8661220987937566
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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