scikit-learn-ts

So I did a lot of ML work in grad school and have also built 4 iOS apps and two web apps. I can tell you building statistical models is not a very interesting grind, it’s mostly cleaning data and fiddling parameters. It’s also unlikely anyone would hire non-stat/math degreed person to do that stuff. On the other hand you’re prob goood at turning models into a. Usable product. Here’s a recent library to do that in NODE https://github.com/transitive-bullshit/scikit-learn-ts

Python's ML ecosystem is generally much more mature than the JS/TS ML ecosystem. As a primarily full-stack TS dev, I've seen first-hand how difficult it is to perform simple ML-related tasks that the Python community takes for granted. So I decided to try an experiment: how well would it work to auto-generate a TypeScript wrapper around Python's scikit-learn package, using a Python subprocess and IPC to communicate back and forth between them? Turns out it works really well in practice, and so scikit-learn-ts was born. The library supports all 257 classes exported by the official Python scikit-learn, and their TS wrappers are all auto-generated from the Python API docs. This project's a lil hacky, but I've already reached out to the scikit-learn team, and we may experiment with using Pyodide as an alternative backend for the Python bridge