The deployment or placement of a machine learning model to provide inferences on real-world data in real-world environments. Models can be operationalized in a variety of locations and settings and modes from batch mode to real-time, in streaming or hot path analytics, on edge devices, in the cloud, on-premise, on a desktop, or a number of other places wherever the model is required to operate and provide inferences on real-world data.
Glossary of Artificial Intelligence (AI), Machine Learning (ML), and Big Data Terms
Operationalization
