Machine learning model repository

A system for managing data, comprising:

• a network computer, comprising:
• a transceiver that communicates over the network;
• a memory that stores at least instructions;
• and
• one or more processor devices that execute instructions that perform actions, including:
• instantiating an answer engine to perform further actions, including:
• receiving one or more questions and one or more model objects, wherein the one or more model objects are part of a data model that conforms to a model schema;
• receiving a plurality of machine learning (ML) model envelopes based on the one or more questions;
• comparing the data model to parameter models that are associated with each of the plurality of ML model envelopes, wherein the comparison includes a traversal of the data model and one or more of the parameter models;
• selecting one or more of the plurality of ML model envelopes based on the comparison, wherein one or more traversal paths corresponding to the one or more model objects satisfy the parameter models of each of the selected one or more ML model envelopes;
• executing one or more ML models included in each selected ML model envelope to provide score values for the one or more model objects, wherein the score values are included in a report;
• and
• providing selective optimization of one or more of performance or storage size for one or more ML model repositories based on one or more characteristics including one or more of model object usage frequency, number of model objects in a query result, model object size, or model object data type, wherein the one or more selective optimizations include one or more of indices to improve identification of each model object to be omitted from the one or more traversal paths, or storing a portion of the one or more model objects in a database or a fast data store;
• and
• the client computer, comprising:
• a client computer transceiver that communicates over the network;
• a client computer memory that stores at least instructions;
• and
• one or more processor devices that execute instructions that perform actions, including:
• providing the one or more questions;
• and
• displaying the visual representation of the report on a hardware display to the user.

A processor readable non-transitory storage media that includes instructions for managing data, wherein execution of the instructions by one or more hardware processors performs actions, comprising:

• instantiating an answer engine to perform further actions, including:
• receiving one or more questions and one or more model objects, wherein the one or more model objects are part of a data model that conforms to a model schema;
• receiving a plurality of machine learning (ML) model envelopes based on the one or more questions;
• comparing the data model to parameter models that are associated with each of the plurality of ML model envelopes, wherein the comparison includes a traversal of the data model and one or more of the parameter models;
• selecting one or more of the plurality of ML model envelopes based on the comparison, wherein one or more traversal paths corresponding to the one or more model objects satisfy the parameter models of each of the selected one or more ML model envelopes;
• executing one or more ML models included in each selected ML model envelope to provide score values for the one or more model objects, wherein the score values are included in a report;
• and
• providing selective optimization of one or more of performance or storage size for one or more ML model repositories based on one or more characteristics including one or more of model object usage frequency, number of model objects in a query result, model object size, or model object data type, wherein the one or more selective optimizations include one or more of indices to improve identification of each model object to be omitted from the one or more traversal paths, or storing a portion of the one or more model objects in a database or a fast data store.

A network computer for managing data, comprising:

• a transceiver that communicates over the network;
• a memory that stores at least instructions;
• and
• one or more processor devices that execute instructions that perform actions, including:
• instantiating an answer engine to perform further actions, including:
• receiving one or more questions and one or more model objects, wherein the one or more model objects are part of a data model that conforms to a model schema;
• receiving a plurality of machine learning (ML) model envelopes based on the one or more questions;
• comparing the data model to parameter models that are associated with each of the plurality of ML model envelopes, wherein the comparison includes a traversal of the data model and one or more of the parameter models;
• selecting one or more of the plurality of ML model envelopes based on the comparison, wherein one or more traversal paths corresponding to the one or more model objects satisfy the parameter models of each of the selected one or more ML model envelopes;
• executing one or more ML models included in each selected ML model envelope to provide score values for the one or more model objects, wherein the score values are included in a report;
• and
• providing selective optimization of one or more of performance or storage size for one or more ML model repositories based on one or more characteristics including one or more of model object usage frequency, number of model objects in a query result, model object size, or model object data type, wherein the one or more selective optimizations include one or more of indices to improve identification of each model object to be omitted from the one or more traversal paths, or storing a portion of the one or more model objects in a database or a fast data store.