Continuous machine learning for extracting description of visual content

Abstract

Aspects of the present disclosure relate to machine learning techniques for continuous implementation and training of a machine learning system for identifying the natural language meaning of visual content. A computer vision model or other suitable machine learning model can predict whether a given descriptor is associated with the visual content. A set of such models can be used to determine whether particular ones of a set of descriptors are associated with the visual content, with the determined descriptors representing a meaning of the visual content. This meaning can be refined based on a multi-armed bandit tracking and analyzing interactions between the visual content and users associated with certain personas related to the determined descriptors.