Julia is a high-level dynamic programming language designed to address the needs of high-performance numerical analysis and computational science. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.
The Julia Programming Language
Course 18.S191 at MIT, Fall 2022 - Introduction to computational thinking with Julia
Interactive data visualizations and plotting in Julia
Bayesian inference with probabilistic programming.
Coding assistance for JupyterLab (code navigation + hover suggestions + linters + autocompletion + rename) using Language Server Protocol
Powerful convenience for Julia visualizations and data analysis
A general-purpose probabilistic programming system with programmable inference
Curated decibans of Julia programming language.
Julia extension for Visual Studio Code
(yet another) static site generator. Simple, customisable, fast, maths with KaTeX, code evaluation, optional pre-rendering, in Julia.
⚡ Single-pass algorithms for statistics
Learn Julia the hard way!
A benchmarking framework for the Julia language
HDF5-compatible file format in pure Julia
A Julia style guide that lives in a blue world
Book on Julia for Data Science
Algorithms implemented in the Julia programming language. We're collaborating with the Humans of Julia community!
The open source version of book `Julia Programming Basics`
Created by Jeff Bezanson, Stefan Karpinski, Viral B. Shah, Alan Edelman
Released February 14, 2012