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There’s no single way to build and operationalize ML models, but there is a consistent need to gather and prepare data, develop models, turn models into intelligent applications, and derive revenue from those applications.
Adopting MLOps practices means there’s no time wasted building or deploying a model and keeping it up to date.
Discover in this product overview how Red Hat OpenShift, a leading hybrid cloud application platform powered by Kubernetes, includes key capabilities to help your organization establish MLOps in a consistent way across data centers, public cloud computing, and edge computing.