Wikis
Info-nuggets to help anyone understand various concepts of MLOps, their significance, and how they are managed throughout the ML lifecycle.
MLOps
MLOps is the discipline of deploying and maintaining machine learning models in production efficiently and reliably.
MLOps is a combination of two terms – Machine Learning and Operations. MLOps is the discipline of deploying and maintaining machine learning models in production efficiently and reliably. The approach applies to the entire ML lifecycle management and brings about effective collaboration between data science and operations teams. The application of MLOPs automates the deployment of ML and DL models in large-scale production environments seamlessly and standardizes management processes.
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