#19 · Primary category： Classical Machine Learning Frameworks
MLJ.jl
A Julia machine learning framework
Project last updated：08/27/26
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Why we included this project
Julia has no shortage of machine learning packages, but each one brings its own API. MLJ gives you a single interface covering more than 200 models, including many wrapped from scikit-learn, so you can train, predict, and evaluate without relearning per-package conventions. On top of that, it handles hyperparameter tuning, performance comparison, and pipeline assembly, which saves real time when you are chaining preprocessing steps into a model stack. If you build models yourself, the companion MLJModelInterface package lets you plug your own implementations into the same framework. For teams standardizing on Julia, this makes a solid home base for everyday modeling work.
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