MLOps

A set of practices and tools that enable data scientists and ML engineers to develop, test, and deploy ML models efficiently. MLOps typically focuses on the development side of the model lifecycle, supporting version control, reproducibility, experiment tracking, and automated workflows for model deployment within data science environments.

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