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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
- Model Browser
- Work with Categorical Data
- Evaluate Model Performance
- Compose models
- Log Workflows
- Customization and Extension
Project Samples
Categories
FrameworksFollow MLJ
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