Apple inc. (20240211805). MACHINE LEARNING MODEL CREATION simplified abstract

MACHINE LEARNING MODEL CREATION

Organization Name

apple inc.

Inventor(s)

Michael R. Siracusa of Mountain View CA (US)

Alexander B. Brown of Mountain View CA (US)

Dheeraj Goswami of Cupertino CA (US)

Nathan C. Wertman of Grand Junction CO (US)

Jacob T. Sawyer of Sunnyvale CA (US)

Donald M. Firlik of Cupertino CA (US)

MACHINE LEARNING MODEL CREATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240211805 titled 'MACHINE LEARNING MODEL CREATION

The patent application describes a system for creating machine learning models that can be easily integrated into applications.

• Developers can choose from a variety of machine learning templates tailored to different types of data, such as images, text, sound, motion, and tabular data.
• A user-friendly interface allows for the selection of training and validation data, as well as the seamless integration of the trained model into the application.
• The system provides numerical scores for both training and validation accuracy, helping developers assess the performance of their models.
• A live mode enables testing of the machine learning model on mobile devices using data from sensors like the camera or microphone.

Potential Applications: - This technology can be used in various industries such as healthcare, finance, and retail for tasks like image recognition, sentiment analysis, and predictive maintenance. - It can also be applied in security systems for identifying anomalies in surveillance footage or detecting fraudulent activities.

Problems Solved: - Simplifies the process of creating and integrating machine learning models into applications. - Provides a user-friendly interface for developers to train and test their models effectively.

Benefits: - Streamlines the development process for machine learning applications. - Allows for quick testing and validation of models on mobile devices. - Enhances the accuracy and efficiency of machine learning tasks.

Commercial Applications: - This technology can be marketed to software development companies, data analytics firms, and mobile app developers looking to incorporate machine learning capabilities into their products.

Questions about Machine Learning Model Creation: 1. How does this system compare to existing tools for creating machine learning models? 2. What are the key factors to consider when selecting a machine learning template for a specific type of data?

Original Abstract Submitted

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.