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Julia was designed for high performance Gamma), and supports complex numbers right out of the box Julia programs automatically compile to efficient native code via llvm, and support multiple platforms
Julia is dynamically typed, feels like a scripting language, and has good support for interactive use, but can also optionally be separately compiled. Click here to learn more. Similar to r programming language, julia is used for statistical computations and data analysis.
The main homepage for julia can be found at julialang.org
This is the github repository of julia source code, including instructions for compiling and installing julia, below. Julia is a scientific programming language comparable to python, matlab, fortran, and r It was originally created in 2012 by jeff bezanson, stefan karpinski, viral shah (and others) in the mit computational science and aritifical intelligence lab (csail) as an open source project. A dynamic language, julia is relatively easy for programmers to learn and adapt.
Jane herriman is director of diversity and outreach at julia computing and a phd student at caltech She is a julia, dance, and strength training enthusiast. The official website for the julia language Julia is a language that is fast, dynamic, easy to use, and open source
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