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/) and Flux Julia's answer to PyTorch/Tensorflow (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.