EthicalML/sml-security

MLOps Cookiecutter Template: A Base Project Structure for Secure Production ML Engineering

35
/ 100
Emerging

This project helps MLOps engineers quickly set up a robust and secure foundation for deploying machine learning models into production environments. It provides a pre-configured project structure that takes trained ML models and transforms them into secure, containerized ML services ready for deployment. The primary users are MLOps engineers, machine learning engineers, and platform engineers responsible for operationalizing ML.

No commits in the last 6 months.

Use this if you are an MLOps or ML engineer needing to rapidly establish a new project for deploying a machine learning model as a secure, production-ready service.

Not ideal if you are a data scientist primarily focused on model training and experimentation, or if you need to deploy models to a highly specialized, non-containerized environment.

MLOps Machine Learning Deployment ML Security Production ML Model Serving
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 11 / 25

How are scores calculated?

Stars

42

Forks

5

Language

Python

License

Apache-2.0

Last pushed

Nov 13, 2024

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/mlops/EthicalML/sml-security"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.