How to version control machine learning projects with code and configurations?

Version control machine learning projects with code and configurations using KitOps

This task can be performed using KitOps

Simple, secure, and reproducible packaging for AI/ML projects

Best product for this task

KitOps

An open source DevOps tool that packages and versions your AI/ML model, datasets, code, and configuration into a reproducible artifact called a ModelKit

What to expect from an ideal product

  1. Creates a single package that bundles your model, data and code into a versioned snapshot
  2. Tracks changes to ML configurations and model parameters over time
  3. Makes it easy to reproduce exact model training conditions later
  4. Helps teams collaborate by keeping model assets organized and documented
  5. Saves model versions as ModelKit artifacts you can reference and roll back to

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