In production machine learning systems, the model itself is only a small part of the implementation. The "scaffolding" required to run machine learning models, also called machine learning operations or MLOps, is another crucial component.
This scaffolding includes configuration, data collection, feature extraction, data verification, machine resource management, analysis tools, process management tools, serving infrastructure and monitoring, explained Dr. Yindalon Aphinyanaphongs, assistant professor for the departments of population health and medicine in the division of general internal medicine at NYU Langone Health.
How the cloud helps machine learning
"A common way of deploying machine learning-based models is to use infrastructure-as-a-service resources," he noted. "Several cloud providers, such as Microsoft Azure and Amazon Sagemaker,...