Machine Learning Operations, often abbreviated as MLOps, refers to the practices and tools that streamline the deployment, monitoring, and management of machine learning models in production. It combines principles from DevOps and machine learning to ensure that models are not only built effectively but also maintained and updated as needed. The goal of MLOps is to enhance collaboration between data scientists and IT operations, making it easier to integrate machine learning into business processes. This includes automating workflows, ensuring model performance, and facilitating continuous integration and delivery of machine learning solutions.