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

Interactive data visualizations and plotting in Julia

Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)

Powerful convenience for Julia visualizations and data analysis

21st century AD

Symbolic programming for the next generation of numerical software

A Julia package for probability distributions and associated functions.

Forward Mode Automatic Differentiation for Julia

Statically sized arrays for Julia

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.

Symbolic expressions, rewriting and simplification

Julia bindings for the Enzyme automatic differentiator

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

Julia functional programming infrastructures and metaprogramming facilities

A data structure for mathematical optimization problems

Filter design, periodograms, window functions, and other digital signal processing functionality

Heterogeneous programming in Julia

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

Special mathematical functions in Julia

Efficient implementation of struct arrays in Julia

Reusable array functionality for Julia's various GPU backends.

JSON parsing and printing

MacroTools provides a library of tools for working with Julia code and expressions.

Polynomial manipulations in Julia

Lazy arrays and linear algebra in Julia

An interface for tables in Julia

Library for validated numerics using interval arithmetic

Julia bindings to the FFTW library for fast Fourier transforms

Adaptive 1d numerical Gauss–Kronrod integration in Julia

AD-backend agnostic system defining custom forward and reverse mode rules. This is the light weight core to allow you to define rules for your functions in your packages, without depending on any particular AD system.

Mathematical functions related to statistics.

Scalable symbolic-numeric set computations in Julia

A combinatorics library for Julia

Tools for easily handling objects like arrays of arrays and deeper nestings in scientific machine learning (SciML) and other applications