https://github.com/JuliaAI/MLJ.jl

A Julia machine learning framework
https://github.com/JuliaAI/MLJ.jl

classification clustering data-science ensemble-learning julia machine-learning pipeline pipelines predictive-modeling regression stacking statistics tuning tuning-parameters

Last synced: 12 days ago
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A Julia machine learning framework

• Host: GitHub
• URL: https://github.com/JuliaAI/MLJ.jl
• Owner: JuliaAI
• License: other
• Created: 2018-08-01T06:29:39.000Z (almost 6 years ago)
• Default Branch: dev
• Last Pushed: 2024-05-05T20:58:44.000Z (17 days ago)
• Last Synced: 2024-05-05T21:39:02.964Z (17 days ago)
• Topics: classification, clustering, data-science, ensemble-learning, julia, machine-learning, pipeline, pipelines, predictive-modeling, regression, stacking, statistics, tuning, tuning-parameters
• Language: Julia
• Homepage: https://JuliaAI/MLJ.jl/dev/
• Size: 40.5 MB
• Stars: 1,726
• Watchers: 49
• Forks: 156
• Open Issues: 96
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • Code of conduct: CODE_OF_CONDUCT.md
  • Roadmap: ROADMAP.md

Lists

• AI - MLJ - A Julia machine learning framework (Julia / [Tools](#tools-1))
• awesome-machine-learning - MLJ - A Julia machine learning framework. (Julia / [Tools](#tools-1))
• awesome-julia - A Julia machine learning framework
• awesome-sciml - alan-turing-institute/MLJ.jl: A Julia machine learning framework
• awesome-machine-learning - MLJ - A Julia machine learning framework. (Julia)
• awesome-machine-learnings - MLJ - A Julia machine learning framework (Julia / [Tools](#tools-1))
• awesome-machine-learning - MLJ - A Julia machine learning framework. (Julia / [Tools](#tools-1))
• awesome-machine-learning - MLJ - A Julia machine learning framework. (Julia / [Tools](#tools-1))
• awesome-stars - alan-turing-institute/MLJ.jl - A Julia machine learning framework (Julia)

README

        


    



A Machine Learning Framework for Julia



  

    

  

  

    

  

  

    

  

  

    

  



MLJ (Machine Learning in Julia) is a toolbox written in Julia

providing a common interface and meta-algorithms for selecting,

tuning, evaluating, composing and comparing about [200 machine learning

models](https://JuliaAI.github.io/MLJ.jl/dev/model_browser/#Model-Browser)

written in Julia and other languages.

**New to MLJ?** Start [here](https://JuliaAI.github.io/MLJ.jl/dev/).

**Integrating an existing machine learning model into the MLJ

framework?** Start [here](https://JuliaAI.github.io/MLJ.jl/dev/quick_start_guide_to_adding_models/).

**Wanting to contribute?** Start [here](CONTRIBUTING.md). 

**PhD and Postdoc opportunies** See [here](https://sebastian.vollmer.ms/jobs/).

MLJ was initially created as a Tools, Practices and Systems project at

the [Alan Turing Institute](https://www.turing.ac.uk/)

in 2019. Funding has also been provided by a [New Zealand Strategic

Science Investment

Fund](https://www.mbie.govt.nz/science-and-technology/science-and-innovation/funding-information-and-opportunities/investment-funds/strategic-science-investment-fund/ssif-funded-programmes/university-of-auckland/)

awarded to the University of Auckland.

MLJ has been developed with the support of the following organizations:



    

    

    

    

    

    



### The MLJ Universe

The functionality of MLJ is distributed over several repositories

illustrated in the dependency chart below. These repositories live at

the [JuliaAI](https://github.com/JuliaAI) umbrella organization.



    



*Dependency chart for MLJ repositories. Repositories with dashed

connections do not currently exist but are planned/proposed.*






Contributing  •  

Code Organization  • 

Road Map 

#### Contributors

*Core design*: A. Blaom, F. Kiraly, S. Vollmer

*Lead contributor*: A. Blaom

*Active maintainers*: A. Blaom, S. Okon, T. Lienart, D. Aluthge