Abstract: Building machine learning models using a standardized library of machine learning model tools. An Application Programming Interface (API) serves as an interface between one or more computer applications that receive user commands for building machine learning models and the standardized library of tools. The API provides an interface between data scientists tasked with designing machine learning models conceptually and a standardized set of software engineering tools. The API enables incorporation of the relevant standardized software engineering tools to build the machine learning models that have been designed conceptually by the data scientists.

Abstract: Automated configuration and deployment of models for projects of business enterprises. A model deployment configuration framework includes a template generated at a user interface. The template prompts a user to select model configuration aspects and model operating factors, and submit the selected aspects and factors to configure and deploy the model in a computing environment of the enterprise's computer system for packaging, training, scoring, and/or auditing the model in connection with a project of the enterprise.