Is there any relatively small (<2MB with dependencies) multiplatform or at least pure-JVM library that provides me with basic learning+prediction functionality? Like linear regression, gradient descent with like 10 parameters, small data sets. Would be nice if it allowed me to define basic neural networks but that's not necessity. I found libraries like Smile, DiffKt, KotlinDL, ONNX but they're all huge (100MB+) and require native dependencies. I also found KInference but it can't do training at all so I can't fine tune the model on user machine. Usecase: to be embedded in minecraft mod to optimize map tiles prefetching, rendering priority and caching. I have experience in tensorflow and pytorch but they're too big for this project and have native code dependencies. I don't need anything fancy, just some basic functionalities for simple models, small datasets, a few parameters.

You can download Smile with a small size by excluding native (or at least it was possible 1 year ago). But the license is not commercial if I recall. I’ve thought about building such a library but it’s a huge undertaking.

It is hard to define, what is basic neural network, MLP could be implemented shortly, but cnn or transformer based stuff requires a lot of megabytes just code

Yeah, I meant exactly just MLP. Actually most CNN uses should also fit in like 2-5k lines of code There's actually a lot of independent use cases that require a simple solution like that. Maybe I'll just end up making some primitive home-grown solution

Possible ojalgo might fit the bill. Never used its neural network package myself, but checkout this link: https://www.ojalgo.org/2021/08/artificial-neural-network-example-v2/ Might not be < 2MB