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August 17th, 2019

Concuerdo plenamente con lo que dice Simon Wenkel: "es razonable dejar de utilizar Python y avanzar hacia Julia por completo".

Aquí su post https://www.simonwenkel.com/2018/10/05/Julia-for-datascience-machine-learning-and-artificial-intelligence.html
Un buen review de los frameworks para trabajar con DS, ML y AI con Julia.

"Previously, I mentioned that it might be the right time to rethink the choice of programming language(s)especially in the context of AI applications for the physical world/engineering. If it is possible to reach FORTRAN-like computational performances with Julia, then it is reasonable to deprecate Python and move towards Julia entirely.
Where Python is executable pseudocode, Julia is executable math. Models look just like the description in the paper, and you have the full power and simplicity of the Julia language (including control flow, multiple dispatch and macros).
Flux.jl
There are many lists and tutorials out there that refer either to outdated Julia packages with no or limited compatibility with Julia 1.0 or the packages are too shallow for any useful application. Moreover, I missed some description of the packages to avoid checking them all out manually to know what they do. Therefore, I am maintaining this list here. (This list is fluent and will be updated and extended from time to time.)"

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deoxyt2
Juan Rodrigo Anabalón R.
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He estado escribiendo sobre temas de seguridad en Livejournal desde el 2008 y en mi horrible y extinto MSN Spaces desde el 2006. En la actualidad, soy CISO en MonkeysLab y Presidente en ISSA Chile.




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