LIBSVM bindings for Julia

Machine Learning in Julia

A 100%-Julia implementation of Gradient-Boosting Regression Tree algorithms

A spiking neural network simulator written in Julia.

A parallel iterator for large machine learning datasets that don't fit into memory inspired by PyTorch's `DataLoader` class.

Generic UNet implementation written in pure Julia, based on Flux.jl

Sleek implementations of the ZigZag, Boomerang and other assorted piecewise deterministic Markov processes for Markov Chain Monte Carlo including Sticky PDMPs for variable selection

A julia package for representing and manipulating model semantics

A Julia library for handling MIDI files

BayesianNonparametrics in julia

MXNet Julia Package - flexible and efficient deep learning in Julia

Core functionality for the MLJ machine learning framework

Workshop materials for training in scientific computing and scientific machine learning

Julia package for automatically generating Bayesian inference algorithms through message passing on Forney-style factor graphs.

A set of functions to support the development of machine learning algorithms

Heterogeneous ensemble learning for Julia.

Evolve Flux networks from scratch!

Visualization for Flux.Chain neural networks

Help! I'm lost in the flatland!

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Functions and data dependencies for loading various word embeddings (Word2Vec, FastText, GLoVE)

Automatic probabilistic programming for scientific machine learning and dynamical models

A lightweight julia wrapper for WORLD - a high-quality speech analysis, modification and synthesis system

Generic artificial neural networks in Julia

Implementation of the Deep Q-learning algorithm to solve MDPs

Online solver based on Monte Carlo tree search for POMDPs with continuous state, action, and observation spaces.

Example of distributed learning in Julia

Mel Frequency Cepstral Coefficients calculation for Julia

Reverse-mode automatic differentiation in Julia

Turing + Makie = Turkie

Deep RNN, LSTM, GRU, GF-RNN, and GF-LSTMs in Julia

Read ONNX graphs in Julia

Automatic detection of sparsity in pure Julia functions for sparsity-enabled scientific machine learning (SciML)

Utility package for subsetting, resampling, iteration, and partitioning of various types of data sets in Machine Learning

Transformations to contrained variables from ℝⁿ.

A operator overloading, tape-based, reverse-mode AD

Machine learning kernels in Julia.

Machine learning kernels in Julia.

Utility package for generating, loading, splitting, and processing Machine Learning datasets

Deep Learning for Julia