As I discussed in “What is Julia?,” Julia is a free open source high-level, high-performance dynamic programming language for numerical computing that combines the development convenience of a dynamic language with the performance of a compiled statically typed language. It was designed to be good for scientific computing, machine learning, data mining, large-scale linear algebra, distributed computing, and parallel computing, and to have the ease of use of Python, R or even Matlab.

There are five major options for working with Julia: JuliaBox online; an installation of the Julia command line; an installation of JuliaPro; Visual Studio Code plus a plug-in and a Julia or JuliaPro installation; and Jupyter notebooks with IJulia. Let’s consider the pros and cons of each.

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