Artificial Intelligence

Artificial intelligence, machine learning, and deep learning frameworks and models.

Organizations¶

alan-turing-institute/MLJ.jl : A Julia machine learning framework by The Alan Turing Institute.
avik-pal/Lux.jl : A explicitly parameterized neural network using deeply nested named tuples.
bcbi/PredictMD.jl : Uniform interface for machine learning in Julia. It is the official machine learning framework of the Brown Center for Biomedical Informatics.
IBM/AutoMLPipeline.jl : a package to create complex ML pipeline structures using simple expressions.
OML-NPA/EasyML.jl : Using machine learning in Julia through a graphical user interface.
ppalmes/CombineML.jl : Create ensembles of machine learning models from scikit-learn, caret, and julia.

FluxML/Flux.jl : Pure Julia ML stack with lightweight abstractions on top of Julia's native GPU and AD support.

FluxML/FastAI.jl : Repository of best practices for deep learning in Julia, inspired by fastai.
FluxML/FluxTraining.jl : A powerful, extensible neural net training backend.
FluxML/GeometricFlux.jl : Geometric Deep Learning for Flux.jl.
FluxML/model-zoo : Various demonstrations of the Flux.jl machine learning library.

denizyuret/Knet.jl : Koç University deep learning framework - A machine learning module implemented in Julia.

cstjean/ScikitLearn.jl : Julia implementation of the scikit-learn API via PyCall.jl.
dmlc/XGBoost.jl : a Julia interface of XGBoost, an efficient and scalable implementation of distributed gradient boosting framework. Julia Con 2023 Video
DrChainsaw/ONNXNaiveNASflux.jl : Import/export ONNX models for Flux.jl.
FluxML/ONNX.jl : Read ONNX graphs and load these models in Julia.
innerlee/LIBLINEAR.jl : Julia binding to Liblinear, a library for Large Linear Classification.
JuliaML/LIBSVM.jl : Julia bindings for LIBSVM C library.
jw3126/ONNXRunTime.jl : Julia bindings for the onnxruntime to perform inference.

Evovest/EvoTrees.jl : Boosted decision trees in Julia.
JuliaAI/DecisionTree.jl : Julia implementation of Decision Tree (CART) and Random Forest algorithms.
JuliaStats/Clustering.jl: Basic functions for clustering data e.g, k-means, dp-means, etc..
KristofferC/NearestNeighbors.jl : High performance nearest neighbor data structures and algorithms for Julia.

JuliaML/MLDatasets.jl : Utility package for accessing common Machine Learning datasets in Julia.
JuliaML/MLLabelUtils.jl : Utility package for working with classification targets and label-encodings.

dfdx/Boltzmann.jl : Restricted Boltzmann Machines and Deep Belief Networks in Julia
irhum/TopoChains.jl : A flexible data structure for multi-input multi-output models.
Julia-XAI/ExplainableAI.jl : Explainable AI in Julia.
JuliaGaussianProcesses/KernelFunctions.jl : Kernel functions for machine learning.
JuliaML/LossFunctions.jl : Julia package of loss functions for machine learning. Documentation
JuliaML/ValueHistories.jl : Utilities to efficiently track learning curves or other optimization information.
mcreel/SimulatedNeuralMoments.jl : Bayesian and classical estimation and inference based on statistics that are filtered through a trained neural net.
mrtzh/PrivateMultiplicativeWeights.jl : Differentially private synthetic data.
sisl/Discretizers.jl : A package to support discretization methods and mapping functions for data discretization and label maps.
sisl/NeuralVerification.jl : verifying whether a neural network satisfies certain input-output constraints. JuliaCon 2021 video.
slimgroup/InvertibleNetworks.jl : Building blocks for invertible neural networks in the Julia programming language.
trappmartin/SumProductNetworks.jl : Sum-Product Networks (deep probabilistic networks) package in Julia.
zgornel/NetworkLearning.jl : Baseline collective classification library, including observation-based learning and entity-based learning.

andrewcooke/ParserCombinator.jl : A parser combinator library.
dellison/DependencyTrees.jl : A package for dependency parsing.
domluna/GloVe.jl : Implements Global Word Vectors.
JuliaNeighbors/BKTrees.jl : Julia implementation of Burkhard-Keller trees.
JuliaText/CorpusLoaders.jl : A variety of loaders for various NLP corpora.
JuliaText/Languages.jl : A package for working with human languages.
JuliaText/TextAnalysis.jl : A Julia package for text analysis.
JuliaText/Word2Vec.jl : Julia interface to word2vec.
JuliaText/WordNet.jl : A Julia package for Princeton's WordNet®.
sbos/AdaGram.jl : Adaptive Skip-gram implementation in Julia.
slycoder/TopicModels.jl : Topic models are Bayesian, hierarchical mixture models of discrete data.
zgornel/ConceptnetNumberbatch.jl : Julia interface to ConceptnetNumberbatch.
zgornel/Glowe.jl : Julia interface to Global Word Vectors.
zgornel/StringAnalysis.jl : A hard fork of the TextAnalysis.jl package, designed to provide a richer, faster and orthogonal API.

TorkelE/Why.jl : A simple function, why(), which gives randomly generated answers.
TotalVerb/EnglishText.jl : Utilities for English-language quirks in Julia.

idiap/TIDIGITSRecipe.jl : A Julia recipe for training an ASR system using the TIDIGITS database.
JuliaDSP/MFCC.jl : Standard Mel Frequency Cepstral Coefficients feature extraction for speech analysis.
r9y9/WORLD.jl : A Julia wrapper for WORLD - a high-quality speech analysis, modification and synthesis system.

AStupidBear/SpikingNeuralNetworks.jl : Julia Spiking Neural Network Simulator.
Dhruva2/NeuronBuilder.jl : building small networks of detailed, conductance-based neurons out of ion channels and synapses.
JuliaNeuroscience/SpikeSynchrony.jl : Measuring distances, synchrony and correlation between spike trains.
leaflabs/WaspNet.jl : fixed-time-step simulations of primarily spiking neural networks (SNNs).
wsphillips/Conductor.jl : a Julia-based neuronal network simulator engine.