Abstract: A system can include a data processing system that can include memory and one or more processors to generate, by a first model trained using machine learning and compatible with first data having a first type and second data having a second type, a first metric based on the first data and indicating a first fault probability in a second model, generate, by the first model, a second metric based on the second data and indicating a second fault probability in a third model, determine, based on the first metric and the second metric, that an aggregate model that includes the second model and the third model satisfies a heuristic indicating a third fault probability in the aggregate model, and instruct, in response to a determination that the aggregate model satisfies the heuristic, a user interface to present an indication that the aggregate model satisfies the heuristic.

Abstract: Methods for automatically generating documentation for a computer-implemented model are provided. In some embodiments, automatically generating documentation for a computer-implemented model includes receiving user input indicative of selection of the computer-implemented model, receiving user input indicative of selection of a documentation template including synthetic content placeholders, and automatically generating documentation for the computer-implemented model by automatically generating synthetic content for each of the synthetic content placeholders based on one or more characteristics of the computer-implemented model, and automatically populating the synthetic content placeholders with the synthetic content.