Data object creation and recommendation using machine learning based offline evolution

Abstract

The technology disclosed relates to neural network-based systems and methods of preparing a data object creation and recommendation database. Roughly described, it relates to, for each of a plurality of preliminary data object images, providing a representation of the image in conjunction with a respective conformity parameter indicating level of conformity of the image with a predefined goal, training a neural network system with the preliminary data object image representations in conjunction with their respective conformity parameters, to evaluate future data object image representations for conformity with the predefined goal, selecting a subset of secondary data object image representations, from a provided plurality of secondary data object image representations, in dependence upon the trained neural network system, and storing the image representations from the selected subset of secondary data object image representations in a tangible machine readable memory for use in a data object creation and recommendation system.