Relax! Flux is the ML library that doesn't make you tensor

A Julia machine learning framework

Koç University deep learning framework.

Deep Learning framework for Julia

BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors

A generic, simple and fast implementation of Deepmind's AlphaZero algorithm.

Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

A Julia wrapper for TensorFlow

Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

Repository of best practices for deep learning in Julia, inspired by fastai

A reinforcement learning package for Julia

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

Julia Implementation of Transformer models

Elegant & Performant Scientific Machine Learning in Julia

Julia bindings for the Enzyme automatic differentiator

Julia package with selected functions in the R package `rethinking`. Used in the SR2... projects.

Julia package for text analysis

MXNet Julia Package - flexible and efficient deep learning in Julia

A package that makes it trivial to create and evaluate machine learning pipeline architectures.

A Julia package for data clustering

Julia implementation of Decision Tree (CART) and Random Forest algorithms

Computer vision models for Flux

A differentiable physics engine for robotics

Simple chains

Utility package for accessing common Machine Learning datasets in Julia

Graph Neural Networks in Julia

Abstract types and methods for Gaussian Processes.

Sensible extensions for exposing torch in Julia.

Reservoir computing utilities for scientific machine learning (SciML)

Abstractions, algorithms, and utilities for reinforcement learning in Julia

Neural Network primitives with multiple backends

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

Boosted trees in Julia

Adaptive Skip-gram implementation in Julia

Julia hybrid constraint programming solver enhanced by a reinforcement learning driven search.

Core functionality for the MLJ machine learning framework

Reverse-mode automatic differentiation in Julia

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

A Julia framework for invertible neural networks

Julia package of loss functions for machine learning.