A Julia machine learning framework

Core functionality for the MLJ machine learning framework

A place for non-native implementations of the MLJ model API

An API for dispatching on the "scientific" type of data instead of the machine type

Hyperparameter optimization algorithms for use in the MLJ machine learning framework

Piecewise Deterministic Sampler library (Bouncy particle sampler, Zig Zag sampler, ...)

Generalized Linear Regressions Models (penalized regressions, robust regressions, ...)

Machine Learning with Time Series in Julia

Package providing K-nearest neighbor regressors and classifiers, for use with the MLJ machine learning framework.

Implementation of the MLJ scientific type convention

Lightweight package to interface with MLJ

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MLJ Interface for ScikitLearn.jl

Repository implementing MLJ interface for MultivariateStats models.

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An implementation of the MLJ model interface for support vector machines provided by LIBSVM.jl