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 written in Julia and other languages. The functionality of MLJ is distributed over several repositories illustrated in the dependency chart below. These repositories live at the JuliaAI umbrella organization.

Features

  • A Machine Learning Framework for Julia
  • Documentation available
  • Integrate an existing machine learning model into the MLJ framework
  • Examples available
  • Simple User Defined Models
  • Customization and Extension
  • Meta-algorithms

Project Samples

Project Activity

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Categories

Machine Learning

License

MIT License

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Julia

Related Categories

Julia Machine Learning Software

Registered

2024-08-14