> the Python ecosystem is often far superior to both
What would you say does the Python ecosystem have that the others are missing? The obvious thing is pytorch/tensorflow/.... I can't think of much else though.
What would you say does the Python ecosystem have that the others are missing? The obvious thing is pytorch/tensorflow/.... I can't think of much else though.
Julia has Flux, which is great. To create a neural network with Flux, you write the forward operation however you want and just auto differentiate the whole thing automatically and get a trainable net.
It is extremely flexible and intuitive.
What Julia lacks is everything which isn't numerical analysis though.
I'm still curious what concrete things you mean that Julia is missing. Maybe I'm so stuck doing numerical analysis, can't think of anything else...
Basically everything not related to numerical analysis. The problem isn't that there isn't an option which does work, but that those options aren't fully developed and mature to actually use for a commercial project.
E.g. look at GUI libraries, the native ones are just wrappers around other libraries and poorly documented. There is a single web framework, but is that supported enough that you would bet your entire company on it being continually supported?
If you are doing anything which isn't related to numerical analysis, Julia isn't your first choice, it also isn't your second or third choice. And I think that is fine, clearly Julia wants to be a good at a particular thing and has achieved that.
Not so simple as it sounds. A lot of speed advantages of Julia comes from doing in place ops on arrays and Zygote does not work with in place updates. So you end up copying and then at that point Python + PyTorch becomes a superior choice as Python is the de facto the universal language.
Pytorch and tensorflow are important and a very good reason to use python or C++, but those two being unavailable is more impactful for the industry, of course your research might need them, but it might very well not.