A Julia machine learning framework

Koç University deep learning framework.

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

A Julia wrapper for TensorFlow

Universal neural differential equations 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

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

MXNet Julia Package - flexible and efficient deep learning in Julia

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

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

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

A Julia package for data clustering

Julia bindings for the Enzyme automatic differentiator

Explicitly Parameterized Neural Networks in Julia

Computer vision models for Flux

A differentiable physics engine for robotics

Utility package for accessing common Machine Learning datasets in Julia

Simple chains

Abstract types and methods for Gaussian Processes.

Sensible extensions for exposing torch in Julia.

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

Reservoir computing utilities for scientific machine learning (SciML)

Graph Neural Networks in Julia

Reverse-mode automatic differentiation in Julia

Deep Learning for Julia

Boosted trees in Julia

Core functionality for the MLJ machine learning framework

Julia package of loss functions for machine learning.

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

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

Wrapping deep learning models from the package Flux.jl for use in the MLJ.jl toolbox

Julia Machine Learning library

Starter kit for legendary models

Evaluating Robustness of Neural Networks with Mixed Integer Programming

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

A flexible neural net training library inspired by fast.ai

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

Julia wrapper for fitting Lasso/ElasticNet GLM models using glmnet

Easy peasy logging to TensorBoard with Julia