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Re:NumPy Illustrated: The Visual Guide to NumPy by dklend122 on Wednesday December 30, 2020 @08:46AM (#25581596)
Mathematical programming in Julia is just more natural and integrated with the language and type system.

From dot broadcasting, to multiple dispatch, to parametric types (if you want ), multidimensional array comprehensions. No worrying about 4 different container types (list, np array, pytorch tensor, symbolic etc etc)

Everything works with one array abstraction, including gpu and multi threaded

Re:NumPy Illustrated: The Visual Guide to NumPy by fishmaster on Thursday December 31, 2020 @10:51AM (#25593723)
This is what I mean with it being more natural and elegant in Julia. Also, "@code_warntype" is incredibly useful for efficient code.