MLOps (Machine Learning Operations) is an emerging technology that enables organizations to deploy, manage, and monitor machine learning applications at scale. It provides a set of tools and processes to automate the entire lifecycle of ML projects, from experimentation to deployment. This helps developers and data scientists to quickly turn their ideas into production-ready ML applications. MLOps can help streamline the development process, reduce operational costs, and increase the agility of the ML-driven products. It also provides better governance and visibility into the ML pipelines, making it easier to troubleshoot and optimize them. With MLOps, developers can develop, train, and deploy ML models faster, and with fewer errors.
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