(now superseded by MLJLinearModels)
Julia learning resources collected from various Julia Computing repos!
MLJ.jl interface for JLBoost.jl
SossMLJ makes it easy to build MLJ machines from user-defined models from the Soss probabilistic programming language
A Least Squares Support Vector Machine implementation in pure Julia
Binary Classification applying dimensionality reduction and hyperparameter tunning, working on MLJ framework in Julia. The Data comes from a Sonar System
Repository implementing MLJ interface for MultivariateStats models.
One package to train them all
Package providing K-nearest neighbor regressors and classifiers, for use with the MLJ machine learning framework.
Julia Toolkit with fairness metrics and bias mitigation algorithms
MLJ.jl interface for GLM.jl models
Generalized Linear Regressions Models (penalized regressions, robust regressions, ...)
A set of tutorials to show how to use Julia for data science (DataFrames, MLJ, ...)
Core functionality for the MLJ machine learning framework
Hyperparameter optimization algorithms for use in the MLJ machine learning framework
An API for dispatching on the "scientific" type of data instead of the machine type
Connecting MLJ and MLFlow
Home of the MLJ model registry and tools for model queries and mode code loading
Repository housing feature selection algorithms for use with the machine learning toolbox MLJ.
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