I built an ML pipeline automation framework – how can I improve it?

Hi HN,

I’m working on an open-source ML automation framework called MLFCrafter.

It’s designed to help build modular, reusable machine learning pipelines using components like CleanerCrafter, ScalerCrafter, ModelCrafter, all connected via a MLFChain.

Here’s the repo: https://github.com/brkcvlk/MLFCrafter

I’d love feedback on:

What features would make this more useful for real-world ML projects?

How can I improve usability and adoption?

Tips on growing an open-source project from solo development to a widely used framework?

Thanks in advance for any advice or thoughts!