Machine Learning Operations (MLOps) is a set of practices that aims to automate and streamline the end-to-end machine learning lifecycle. This includes data preparation, model building, validation, deployment, and monitoring. MLOps focuses on bridging the gap between experimentation and production, enabling faster and more reliable deployment of machine learning models at scale, improving model governance and ensuring consistent performance over time.
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