ML Ops

ML Ops, or Machine Learning Operations, is the practice of managing and maintaining machine learning models throughout their lifecycle. It involves tasks like developing, testing, deploying, monitoring, and updating models to ensure they perform accurately and reliably over time. Think of it as combining software engineering with data science to streamline how machine learning systems are built and kept running smoothly. ML Ops helps organizations deliver smart solutions faster, maintain quality, and adapt models as new data or requirements emerge.