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Ecosystem of numerical methods for microbial kinetics data analysis, from preprocessing to result interpretation.

Adds support for parallelization for Taija packages.

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A decision-making framework for the cost-efficient design of experiments, balancing the value of acquired experimental evidence and incurred costs.

A package with exported learning networks that combine resampling methods from Imbalance.jl and classification models from MLJ

A package for plotting custom symbols from Taija packages.

Connecting MLJ and MLFlow

A Julia toolbox with resampling methods to correct for class imbalance.

Measures (metrics) for statistics and machine learning

Advanced exports management for AutomationLabs.jl

This is a dimensionality reduction algorithm which has the goal of maintaining interpretability i.e we eliminate variables directly from potential models that don't seem to add any predictive power.

One package to train them all

Interpretable Machine Learning via Rule Extraction

A Julia package for Generative Topographic Mapping

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Warehouse for dynamical systems identification and control

A powerful, no code solution for control and systems engineering

Dynamical systems identification

Predictive Uncertainty Quantification through Conformal Prediction for Machine Learning models trained in MLJ.

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ADRIA: Adaptive Dynamic Reef Intervention Algorithms. A multi-criteria decision support platform for informing reef restoration and adaptation interventions.

An unofficial Julia wrapper for the RAPIDS.ai ecosystem using PythonCall.jl

Utilities to test implementations of the MLJ model interface and provide integration tests for the MLJ ecosystem

Effortless Bayesian Deep Learning through Laplace Approximation for Flux.jl neural networks.

A package for Counterfactual Explanations and Algorithmic Recourse in Julia.

A Julia package for modelling Algorithmic Recourse Dynamics.

Implementations of Infinitesimal Continuous Normalizing Flows Algorithms in Julia

Test Toolkit for Outlier Detection Algorithms

A pure Julia implementation of the Targeted Minimum Loss-based Estimation

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Easy way to use public outlier detection datasets with Julia

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A package for wrapping iterative MLJ models in a control strategy

Fast, scalable and flexible Outlier Detection with Julia

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Invariant Causal Prediction in pure Julia

Julia Toolkit with fairness metrics and bias mitigation algorithms