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

Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.

Interactive data visualizations and plotting in Julia

Powerful convenience for Julia visualizations and data analysis

In-memory tabular data in Julia

21st century AD

Optimization functions for Julia

A Julia package for probability distributions and associated functions.

Forward Mode Automatic Differentiation for Julia

Python and Julia in harmony.

Statically sized arrays for Julia

Macro(s) for vectorizing loops.

Julia implementation of Data structures

Formatted output of timed sections in Julia

HTTP for Julia

A benchmarking framework for the Julia language

Physical quantities with arbitrary units

Basic statistics for Julia

Convert julia objects to LaTeX equations, arrays or other environments.

HDF5-compatible file format in pure Julia

High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)

Utility library for working with CSV and other delimited files in the Julia programming language

An optimized graphs package for the Julia programming language

Julia bindings for the Enzyme automatic differentiator

Forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs

A Julia package for evaluating distances (metrics) between vectors.

Types with default field values, keyword constructors and (un-)pack macros

High performance nearest neighbor data structures (KDTree and BallTree) and algorithms for Julia.

Print data in formatted tables.

Julia functional programming infrastructures and metaprogramming facilities

A data structure for mathematical optimization problems

Overdub Your Julia Code

Heterogeneous programming in Julia

Plotting for Julia based on GR, a framework for visualisation applications

Special mathematical functions in Julia

Reverse Mode Automatic Differentiation for Julia

A Julia Basket of Hand-Picked Krylov Methods

A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.

Julia solvers for systems of nonlinear equations and mixed complementarity problems

Efficient implementation of struct arrays in Julia