MLJ: A Julia package for composable machine learning
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Abstract (arXiv)
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.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Jul 2020.
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Citing papers per year: 2021: 4; 2022: 2; 2023: 2; 2024: 0; 2025: 0; 2026: 1.
9 papers.
- 2021How to avoid machine learning pitfalls: a guide for academic researcherscited by 34
- 2021GeCo: Quality Counterfactual Explanations in Real Timecited by 32
- 2023Explaining Black-Box Models through Counterfactualscited by 4
- 2021Designing Machine Learning Toolboxes: Concepts, Principles and Patternscited by 2
- 2022OutlierDetection.jl: A modular outlier detection ecosystem for the Julia programming languagecited by 1
- 2021EBIC.JL -- an Efficient Implementation of Evolutionary Biclustering Algorithm in Juliacited by 0
- 2022A Review of Open Source Software Tools for Time Series Analysiscited by 0
- 2023A knowledge-driven AutoML architecturecited by 0
- 2026mlr3torch: A Deep Learning Framework in R based on mlr3 and torchcited by 0
- 2026mlr3torch: A Deep Learning Framework in R based on mlr3 and torch20 Apr 2026
- 2023A knowledge-driven AutoML architecture28 Nov 2023
- 2023Explaining Black-Box Models through Counterfactuals14 Aug 2023
- 2022OutlierDetection.jl: A modular outlier detection ecosystem for the Julia programming language8 Nov 2022
- 2022A Review of Open Source Software Tools for Time Series Analysis10 Mar 2022
- 2021How to avoid machine learning pitfalls: a guide for academic researchers5 Aug 2021
- 2021EBIC.JL -- an Efficient Implementation of Evolutionary Biclustering Algorithm in Julia3 May 2021
- 2021Designing Machine Learning Toolboxes: Concepts, Principles and Patterns13 Jan 2021
- 2021GeCo: Quality Counterfactual Explanations in Real Time5 Jan 2021