Simple chains

A Julia wrapper for TensorFlow

A Julia package for non-negative matrix factorization

Flux's ex AD

A rewrite of Julia's parser in Julia

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

Mel-Generalized Cepstrum analysis

Julia implementation of the scikit-learn API https://cstjean.github.io/ScikitLearn.jl/dev/

Unofficial Julia bindings for logging experiments to wandb.ai

Home of the MLJ model registry and tools for model queries and mode code loading

A reinforcement learning package for Julia

Monte Carlo Tree Search for Markov decision processes using the POMDPs.jl framework

High-performance reactive message-passing based Bayesian inference engine

A Julia package for data clustering

Create ensembles of machine learning models from scikit-learn, caret, and julia

Utility package for accessing common Machine Learning datasets in Julia

A Julia package for interpretable machine learning with stochastic Shapley values

Utilities and abstractions for Machine Learning tasks

Hyperparameter optimization algorithms for use in the MLJ machine learning framework

Truncated singular value decomposition with partial reorthogonalization

Reservoir computing utilities for scientific machine learning (SciML)

Simple particle filter implementation in Julia - works with POMDPs.jl models or others.

Beta Machine Learning Toolkit

OpenAI API wrapper for Julia

Sensible extensions for exposing torch in Julia.

A package for working with human languages

Pure Julia implementations of single-pass object detection neural networks.

Bayesian optimization for Julia

Evaluating Robustness of Neural Networks with Mixed Integer Programming

A package for time series data processing, classification, clustering, and prediction.

Approximate Bayesian Computation (ABC) algorithms for likelihood free inference in julia

Build flexible hierarchical multi-instance learning models.

Repository housing feature selection algorithms for use with the machine learning toolbox MLJ.

Abstractions, algorithms, and utilities for reinforcement learning in Julia

A Julia framework for invertible neural networks

Gaussian Process package based on data augmentation, sparsity and natural gradients

Cartesian Genetic Programming for Julia

DEPRECATED: Regularised Empirical Risk Minimisation Framework (SVMs, LogReg, Linear Regression) in Julia

Lightweight package to interface with MLJ

Import/export ONNX models