MLOps

MLOps, or Machine Learning Operations, refers to the set of practices, principles, and tools for deploying, managing, and monitoring machine learning models in production environments. MLOps aims to bridge the gap between the development of machine learning models and their operational use by streamlining the end-to-end ML lifecycle. It involves collaboration between data scientists, engineers, and IT operations to automate the deployment process, ensure model reliability, and facilitate continuous integration and delivery (CI/CD) of ML models.