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> Julia for data science

I work in scientific computing, and while me and my colleagues have all experimented with Julia at some level (and definitely welcome having more options), I don't yet know of anyone who has built any part of their permanent toolchain with it yet.

Are there any notable use cases out in the wild yet (known internal use by an organization, or major FOSS tool or framework)?



I won't comment on organizations using Julia, but some conclusions can be drawn from the presenters and sponsors at JuliaCon 2015: http://juliacon.org/2015/

Here is a brief list of some major packages that I am aware of:

- https://github.com/JuliaOpt/JuMP.jl - https://github.com/JuliaOpt/Convex.jl (Stephen Boyd's current and former students) - https://github.com/ApproxFun/ApproxFun.jl (Nick Trefethen's former students) - https://github.com/dmlc/MXNet.jl - http://nemocas.org

Julia has been used (and cited) in at least one Nature publication: http://www.nature.com/nature/journal/v526/n7575/full/nature1...

A larger list (with associated publications): http://julialang.org/publications/

Julia is also being used for courses at a number of universities: http://julialang.org/teaching/




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