willyfh/mlops-workflow
An MLOps workflow for training, inference, experiment tracking, model registry, and deployment.
This project helps MLOps engineers streamline the process of taking machine learning models from development to deployment. It allows you to track experiments, manage model versions, and serve predictions efficiently. You input your machine learning code and data, and it provides a running system for model training, inference, and performance monitoring.
Use this if you are an MLOps engineer or a data scientist looking for a structured, modular workflow to manage the lifecycle of your machine learning models from experimentation to production.
Not ideal if you are a beginner looking for a simple, single-script solution for a one-off model, or if you need a fully managed cloud-based MLOps platform.
Stars
16
Forks
2
Language
Python
License
MIT
Category
Last pushed
Nov 24, 2025
Commits (30d)
0
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