The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 10, 2023

Filed:

Oct. 31, 2019
Applicant:

Apple Inc., Cupertino, CA (US);

Inventors:

Michael R. Siracusa, Mountain View, CA (US);

Alexander B. Brown, Mountain View, CA (US);

Dheeraj Goswami, Cupertino, CA (US);

Nathan C. Wertman, Grand Junction, CO (US);

Jacob T. Sawyer, Sunnyvale, CA (US);

Donald M. Firlik, Cupertino, CA (US);

Assignee:

APPLE INC., Cupertino, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 3/048 (2013.01); G06N 20/00 (2019.01); G06F 3/0486 (2013.01); G06F 8/34 (2018.01); G06F 18/214 (2023.01); G06F 18/21 (2023.01); G06F 18/2431 (2023.01); G06V 10/776 (2022.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 3/048 (2013.01); G06F 3/0486 (2013.01); G06F 8/34 (2013.01); G06F 18/2148 (2023.01); G06F 18/2193 (2023.01); G06F 18/2431 (2023.01); G06V 10/776 (2022.01);
Abstract

Embodiments of the present disclosure present devices, methods, and computer readable medium for techniques for creating machine learning models. Application developers can select a machine learning template from a plurality of templates appropriate for the type of data used in their application. Templates can include multiple templates for classification of images, text, sound, motion, and tabular data. A graphical user interface allows for intuitive selection of training data, validation data, and integration of the trained model into the application. The techniques further display a numerical score for both the training accuracy and validation accuracy using the test data. The application provides a live mode that allows for execution of the machine learning model on a mobile device to allow for testing the model from data from one or more of the sensors (i.e., camera or microphone) on the mobile device.


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