fmind/cookiecutter-mlops-package
A Cookiecutter template that provides a project scaffold for building, testing, packaging, and deploying Python ML projects and Docker images.
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This repository offers a structured starting point for MLOps initiatives, delivering pre-configured directories, CI/CD patterns, and Docker integration tailored for machine learning deployments. It is designed to work with platforms like Kubernetes, Vertex AI, Databricks, Azure ML, and AWS SageMaker by standardizing how Python packages and containers are structured. The template includes guidance for testing, versioning, and deploying ML artifacts in a reproducible manner.
Frequently asked
- What is fmind/cookiecutter-mlops-package?
- A Cookiecutter template that provides a project scaffold for building, testing, packaging, and deploying Python ML projects and Docker images.
- Is cookiecutter-mlops-package open source?
- Yes — fmind/cookiecutter-mlops-package is open source, released under the MIT license.
- What language is cookiecutter-mlops-package written in?
- fmind/cookiecutter-mlops-package is primarily written in Just.
- How popular is cookiecutter-mlops-package?
- fmind/cookiecutter-mlops-package has 443 stars on GitHub.
- Where can I find cookiecutter-mlops-package?
- fmind/cookiecutter-mlops-package is on GitHub at https://github.com/fmind/cookiecutter-mlops-package.