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

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

Powerful convenience for Julia visualizations and data analysis

In-memory tabular data in Julia

21st century AD

A Julia package for probability distributions and associated functions.

Forward Mode Automatic Differentiation for Julia

Statically sized arrays for Julia

Progress meter for long-running computations

Julia implementation of Data structures

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.

Fast, continuous interpolation of discrete datasets in Julia

Statistical plotting recipes for Plots.jl

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

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

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

A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)

Heterogeneous programming in Julia

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

A Julia package for data clustering

Special mathematical functions in Julia

Efficient implementation of struct arrays in Julia

Call R from 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.

An interface for tables in Julia

High accuracy derivatives, estimated via numerical finite differences (formerly FDM.jl)

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.

Specifying, fitting, and evaluating statistical models in Julia

Mathematical functions related to statistics.