Patents by Inventor Jérémy AECK

Jérémy AECK has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Automated data processing and machine learning model generation
    Patent number: 11640563
    Abstract: A device may obtain first data relating to a machine learning model. The device may pre-process the first data to alter the first data to generate second data. The device may process the second data to select a set of features from the second data. The device may analyze the set of features to evaluate a plurality of types of machine learning models with respect to the set of features. The device may select a particular type of machine learning model for the set of features based on analyzing the set of features to evaluate the plurality of types of machine learning models. The device may tune a set of parameters of the particular type of machine learning model to train the machine learning model. The device may receive third data for prediction. The device may provide a prediction using the particular type of machine learning model.
    Type: Grant
    Filed: March 23, 2020
    Date of Patent: May 2, 2023
    Assignee: Accenture Global Solutions Limited
    Inventors: Luke Higgins, Liang Han, Koushik M Vijayaraghavan, Rajendra T. Prasad, Aditi Kulkarni, Gayathri Pallail, Charles Grenet, Jean-Francois Depoitre, Xiwen Sun, Jérémy Aeck, Yuqing Xi, Srikanth Prasad, Pankaj Jetley, Jayashri Sridevi, Easwer Chinnadurai, Niju Prabha
  • AUTOMATED DATA PROCESSING AND MACHINE LEARNING MODEL GENERATION
    Publication number: 20210065053
    Abstract: A device may obtain first data relating to a machine learning model. The device may pre-process the first data to alter the first data to generate second data. The device may process the second data to select a set of features from the second data. The device may analyze the set of features to evaluate a plurality of types of machine learning models with respect to the set of features. The device may select a particular type of machine learning model for the set of features based on analyzing the set of features to evaluate the plurality of types of machine learning models. The device may tune a set of parameters of the particular type of machine learning model to train the machine learning model. The device may receive third data for prediction. The device may provide a prediction using the particular type of machine learning model.
    Type: Application
    Filed: March 23, 2020
    Publication date: March 4, 2021
    Inventors: Luke HIGGINS, Liang HAN, Koushik M VIJAYARAGHAVAN, Rajendra T. Prasad, Aditi KULKARNI, Gayathri PALLAIL, Charles GRENET, Jean-Francois DEPOITRE, Xiwen SUN, Jérémy AECK, Yuqing XI, Srikanth PRASAD, Pankaj JETLEY, Jayashri SRIDEVI, Easwer CHINNADURAI, Niju PRABHA