ggeop/ML-Project-Template
This project contains a blueprint of a production ML structure. Also can guide a user how to organize their code to follow CI/CD best practices.
This project provides a clear blueprint for organizing a Machine Learning project, helping MLOps Engineers, Data Scientists, and Software Engineers structure their code for production. It offers a standardized framework for building, testing, and deploying ML models, especially those with multiple data sources and pipelines. The output is a well-organized, maintainable ML project ready for continuous integration and delivery.
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Use this if you are building an ML project for production and need a robust, standardized way to structure your code and implement CI/CD best practices.
Not ideal if you are working on a small, experimental ML project or do not require continuous integration and deployment workflows.
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Last pushed
Oct 20, 2022
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