Machine learning model remote management in advanced communication networks

A method, comprising:

• publishing, via a communications network by a network system comprising a processor, machine learning model capability data;
• receiving, by the network system, a group of machine learning models and associated model reselection criterion data;
• operating, by the network system for network-related operations, a machine learning model of the group of machine learning models as an active machine learning model;
• and
• evaluating, by the network system, the active machine learning model with respect to the reselection criterion data to determine whether operating with the active machine learning model results in model reselection.

A non-transitory machine-readable medium, comprising executable instructions that, when executed by a processor of a network model host, facilitate performance of operations, the operations comprising:

• publishing machine learning model capability data of the network model host;
• receiving, based on the publishing, a machine learning model in association with machine learning model metadata and machine learning parameter data;
• training the machine learning model using local data to obtain an inference result, wherein the local data is local to the network model host;
• and
• evaluating the inference result with respect to criterion data in the machine learning model metadata.