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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 over 200 machine learning models written in Julia and other languages. The MLJ.jl package is an umbrella package for components distributed in a number of other packages. New to MLJ? Start here. Documentation is here. Integrating an existing machine learning model into the MLJ framework? Start here. AboutA Julia machine learning framework Topicsclassificationclusteringdata-scienceensemble-learningjuliamachine-learningpipelinepipelinespredictive-modelingregressionstackingstatisticstuningtuning-parameters ResourcesCode of conductContributingReleasesPackagesUsed byContributorsLanguages | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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