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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
Categories
Machine LearningLicense
MIT LicenseFollow MLJ.jl
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