In-memory tabular data in Julia

Optimization functions for Julia

A Julia package for probability distributions and associated functions.

Forward Mode Automatic Differentiation for Julia

A documentation generator for Julia.

Statically sized arrays for Julia

Progress meter for long-running computations

Julia implementation of Data structures

A benchmarking framework for the Julia language

Generalized linear models in Julia

Basic statistics for Julia

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

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

Print data in formatted tables.

A data structure for mathematical optimization problems

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

Special mathematical functions in Julia

JSON parsing and printing

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

An interface for tables in Julia

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

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

Fast non-allocating calculations of gradients, Jacobians, and Hessians with sparsity support

Advanced Pattern Matching for Julia

Mathematical functions related to statistics.

Convenient input and display of LaTeX equation strings for the Julia language

Reduce time-to-first-execution of Julia code

Abstract julia interfaces for working with trees

Lazy code loading for Julia

Julia package for lazily representing matrices filled with a single entry

Julia macro for re-exporting one module from another

Julia wrapper around Google's gumbo C library for parsing HTML

Colored and styled strings for terminals.

Simple, fast, column-based storage for data analysis in Julia

Compatibility across Julia versions

Split-apply-combine strategies for Julia

Project Preferences Package

Line search methods for optimization and root-finding