R and Python are still (currently) nicer for stats and ML, although there's a lot of not-yet-mature Julia libraries that are extremely cool (Turing.jl for Bayes

R and Python are still (currently) nicer for stats and ML, although there's a lot of not-yet-mature Julia libraries that are extremely cool (Turing.jl for Bayesian inference in particular, and systems for autodiff). I also think Plots.jl is the best-designed plotting system, although if you are a ggplot true believer you might not agree. But for classical scientific computing, of the sort typically done by real engineers wearing coke-bottle glasses, using MATLAB and expensive toolboxes, it can't be beat. It's really easy to work with matrices and make your code super-fast. And it steals all the good parts of MATLAB syntax but with a good, modern, sensibly designed programming language. Also, DifferentialEquations.jl is undeniably the best available piece of software for solving differential equations, in terms of both performance and ease-of-use. It feels like using alien technology or something.