New
A Continuous Training (CT) pipeline formalises a Machine Learning (ML) model developed through data science experimentation, using the data available at a given point in time. It prepares the model for deployment while enabling autonomous updates as new data becomes available, along with robust performance monitoring, logging, and model registry capabilities for auditing purposes.
InterSystems IRIS already provides nearly all the components required to support such a pipeline. However, one key element is missing: a standardised tool for model registry.