Patents Assigned to MetiStream, Inc.
  • Systems, methods, and apparatuses for training, storage, and interaction with machine learning models
    Patent number: 11501201
    Abstract: A system includes a repository storing trained machine learning models and metadata corresponding to the trained machine learning models. The system provides an interface for performing operations on the trained machine learning models and corresponding metadata stored in the repository, and evaluates trained machine learning models that are linked to the data sources and stored in the repository to obtain resulting predictions for a payload of records of data contained in the data sources. A method includes configuring one or more data sources, ingesting training data from the configured data sources, identifying a scenario for prediction, training one or more machine learning models on the ingested training data for the identified scenario, reviewing performance of the trained machine learning models and storing the trained machine learning models and corresponding metadata in A model repository, and dynamically creating a user interface for interacting with the stored trained machine learning models.
    Type: Grant
    Filed: July 17, 2017
    Date of Patent: November 15, 2022
    Assignee: METISTREAM, INC.
    Inventors: Chiny Driscoll, Donna-M. Fernandez, Nathan G Salmon
  • SYSTEMS, METHODS, AND APPARATUSES FOR TRAINING, STORAGE, AND INTERACTION WITH MACHINE LEARNING MODELS
    Publication number: 20190019106
    Abstract: A system includes a repository storing trained machine learning models and metadata corresponding to the trained machine learning models. The system provides an interface for performing operations on the trained machine learning models and corresponding metadata stored in the repository, and evaluates trained machine learning models that are linked to the data sources and stored in the repository to obtain resulting predictions for a payload of records of data contained in the data sources. A method includes configuring one or more data sources, ingesting training data from the configured data sources, identifying a scenario for prediction, training one or more machine learning models on the ingested training data for the identified scenario, reviewing performance of the trained machine learning models and storing the trained machine learning models and corresponding metadata in A model repository, and dynamically creating a user interface for interacting with the stored trained machine learning models.
    Type: Application
    Filed: July 17, 2017
    Publication date: January 17, 2019
    Applicant: MetiStream, Inc.
    Inventors: Chiny Driscoll, Donna-M Fernandez, Nathan G. Salmon