> write above proper english
I agree. I thought about learning English, but I also thought since ChatGPT is available, why bother learning it? So I decided not to learn it now and just wait for ChatGPT.
The result was...disappointing.
Just asking because I don’t want to start poking at the ML stuff but don’t have any experience/baggage to go along with it.
Maybe I was too broad in my initial statements about pythonic code, because comprehensions for example work pretty much the same as in python, and they are fast. It’s just that if you’re used to mind bending array broadcasting tricks in numpy or whatever, there’s usually a more Julian way to get it done with better simplicity and performance. BenchmarkTools.jl and some of the standard library tools are also really great for getting a sense of what matters
However, I must caution against trying to replace Torch within Julia. The Julia ecosystem does not have these huge libraries for neutral networks yet. Building such a thing requires a huge investment (by a company like Google or Facebook) and Julia is not there yet. You can do neural networks with GPU support in Julia (even with extremely fancy autodiff capabilities) but it's not "production ready" in that you will have to deal with the quickly moving ecosystem and probably even end up contributing to it, if you stick with it long enough to build something interesting.
On the other hand, if you ever wanted to add a "neutral network term" to a PDE to simultaneously solve and train the network, Julia is the place to go. It's crazy what kinds of modeling you could potentially do with stuff like that.