MLOps, or Machine Learning Operations, is a multidisciplinary engineering discipline that ensures reliable and efficient deployment of machine learning models in production.　It combines Data Engineering, Machine Learning, and DevOps to build automated pipelines for continuous integration, delivery, and monitoring. By formalizing lifecycle management, MLOps addresses "technical debt" in AI systems and maintains model performance despite data drift. This approach is vital for converting experimental prototypes into scalable, industrial-grade software.