Trying the Julia language in the notebook
Julia (http://julialang.org) is a young, high-level, dynamic language for high-performance numerical computing. The first version was released in 2012 after three years of development at MIT. Julia borrows ideas from Python, R, MATLAB, Ruby, Lisp, C, and other languages. Its major strength is to combine the expressivity and ease of use of high-level, dynamic languages with the speed of C (almost). This is achieved via an LLVM-based Just-In-Time (JIT) compiler that targets machine code for x86-64 architectures.
In this recipe, we will try Julia in the IPython notebook using the IJulia package available at http://github.com/JuliaLang/IJulia.jl. We will also show how to use Python packages (such as NumPy and ...
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