Powerful convenience for Julia visualizations and data analysis

In-memory tabular data in Julia

CUDA programming in Julia.

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

Formatted output of timed sections in Julia

HTTP for Julia

A benchmarking framework for the Julia language

Physical quantities with arbitrary units

Generalized linear models in Julia

Basic statistics for Julia

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

HDF5-compatible file format in pure Julia

Julia library for stylized terminal output

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

Print data in formatted tables.

A Julia package for fitting (statistical) mixed-effects models

Iterative algorithms for solving linear systems, eigensystems, and singular value problems

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

Root finding functions for Julia

A Julia Basket of Hand-Picked Krylov Methods

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

An interface for tables in Julia

Julia package for Gaussian quadrature

An alternative interface for dictionaries in Julia, for improved productivity and performance

Julia bindings to the FFTW library for fast Fourier transforms

Adaptive 1d numerical Gauss–Kronrod integration in Julia

A Julia interface to the NLopt nonlinear-optimization library

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