A sibling pointed out that there is a bunch of this stuff already in Julia. I’ll add, though, that the ML stuff isn’t quite as mature as the whole Python ecosys

A sibling pointed out that there is a bunch of this stuff already in Julia. I’ll add, though, that the ML stuff isn’t quite as mature as the whole Python ecosystem. In addition to native offerings like Flux, there are bindings to things like PyTorch, and, more generally, calling Python is pretty trivial. I’d say that Julia’s arrays are significantly better than NumPy. Julia’s broadcast operator is like ufuncs except way easier and way faster. The machinery around GPUs is better, too, in my opinion. GPU support isn’t coupled to other concerns like automatic differentiation. You can write generic code in a broadcasting style (which is, again, a lot nicer than NumPy by default) or very easily write your own kernels. Multithreading is also way better than in other scientific computing languages.