The Julia Programming Language

• Still highly imcomplete
• High-level programming language for future astronomer….maybe?

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Basic Information

• The JuliaLab@MIT
• The Julia Programming Language
  • Julia was designed from the beginning for high performance.
  • The source code can be found on Github
• Julia 1.1 Documentation
• Julia Observer
  • Good place to search for useful tools.
• Julia.jl - Curated decibans of Julia programming language
  • Check out the Space-Science.md for astro-related packages.

Distributions

• JuliaPro - A Julia distribution crafted for your success

Learning Materials

• Learn Julia the hard way!
  • GitBook for learning Julia language.
• Julia Cheat Sheet
  • The one page version
• JuliaZH.jl - Julia语言中文文档

Useful Packages

Basic

• DataFrames.jl - In-memory tabular data in Julia
  • Tools for working with tabular data in Julia.
• CSV.jl - Utility library for working with CSV and other delimited files in the Julia programming language
  • A fast, flexible delimited file reader/writer for Julia.
• Genie.jl - The highly productive Julia web framework
  • Genie is a full-stack MVC web framework that provides a streamlined and efficient workflow for developing modern web applications.

Visualization

• Plots.jl - Powerful convenience for Julia visualizations and data analysis
  • Documents can be found here
• Gadfly.jl - Crafty statistical graphics for Julia
  • Gadfly is a plotting and data visualization system written in Julia.

Optimization

• Optim.jl - Optimization functions for Julia
  • Optim.jl is a package for univariate and multivariate optimization of functions.
• LsqFit.jl - Simple curve fitting in Julia
  • The LsqFit package is a small library that provides basic least-squares fitting in pure Julia under an MIT license.

Statistics

• Turing.jl - The Turing language for probabilistic programming
  • Turing allows the user to write models in standard Julia syntax, and provide a wide range of sampling-based inference methods for solving problems across probabilistic machine learning, Bayesian statistics and data science etc.

Machine Learning

• Flux.jl - the ML library that doesn’t make you tensor
  • Flux is an elegant approach to machine learning. It’s a 100% pure-Julia stack, and provides lightweight abstractions on top of Julia’s native GPU and AD support.
• knet.jl - Koç University deep learning framework
  • Knet (pronounced “kay-net”) is the Koç University deep learning framework implemented in Julia by Deniz Yuret and collaborators