It compares quite favorably. The nice thing is that most of Numpy and Octave functionality is already builtin to Julia (multidimensional matrices are first clas

It compares quite favorably. The nice thing is that most of Numpy and Octave functionality is already builtin to Julia (multidimensional matrices are first class as they are in Matlab/Octave). Julia performance is quite good and multiple dispatch is great for composing packages (once you get used to it). Check out SciML, Julia's answer to scipy (https://sciml.ai/ https://sciml.ai/) and Flux Julia's answer to PyTorch/Tensorflow (https://fluxml.ai/ https://fluxml.ai/). Are these projects as mature as their Python counterparts? To be honest, no they're not, but they are making pretty rapid progress.