MLOps

MLOps, or Machine Learning Operations, is a set of practices that aim to deploy and maintain machine learning models in production reliably and efficiently. It combines principles from DevOps with machine learning to streamline the process of bringing models from development to deployment. Key characteristics of MLOps include automation of the deployment process, monitoring of model performance, and collaboration between data scientists and IT operations teams. Common use cases for MLOps include continuous integration and continuous delivery (CI/CD) for machine learning projects, automated retraining of models based on new data, and ensuring compliance and governance in model management.