= ModelOps
{wiki=ModelOps}
ModelOps, short for Model Operations, refers to the set of practices, tools, and processes that organizations use to manage and deploy machine learning models effectively and at scale. It encompasses various aspects of the machine learning lifecycle, including model development, deployment, monitoring, and governance. Key components of ModelOps include: 1. **Model Deployment**: The process of integrating machine learning models into production environments, making them accessible for usage in real-time applications or batch processing systems.
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