18587613. SYSTEMS AND METHODS FOR A MACHINE LEARNING FRAMEWORK simplified abstract (Walmart Apollo, LLC)
Contents
SYSTEMS AND METHODS FOR A MACHINE LEARNING FRAMEWORK
Organization Name
Inventor(s)
Vahid Jalalibarsari of Sunnyvale CA (US)
SYSTEMS AND METHODS FOR A MACHINE LEARNING FRAMEWORK - A simplified explanation of the abstract
This abstract first appeared for US patent application 18587613 titled 'SYSTEMS AND METHODS FOR A MACHINE LEARNING FRAMEWORK
The patent application describes a system that utilizes machine learning algorithms to process feature data and historical transactions.
- Receiving a configuration file over a computer network to identify feature data for machine learning.
- Identifying feature data using the configuration file.
- Storing feature data and historical transactions in an output file on storage devices.
- Transmitting the output file over the network for use in a machine learning application.
- Generating a machine learning algorithm for a model based on parameters in the output file.
Potential Applications: - Financial forecasting - Fraud detection - Customer behavior analysis
Problems Solved: - Efficient processing of large datasets - Automation of machine learning model generation
Benefits: - Improved accuracy in predictions - Time and cost savings in data analysis
Commercial Applications: Title: "Enhanced Machine Learning System for Data Analysis" This technology can be used in various industries such as finance, e-commerce, and healthcare for predictive analytics and decision-making processes.
Questions about the technology: 1. How does this system improve the efficiency of machine learning model generation? 2. What are the key advantages of using historical transactions in the machine learning process?
Original Abstract Submitted
A system including one or more processors; and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations: receiving, over a computer network, a configuration file to identify feature data for use in a machine learning algorithm; identifying, using the configuration file, the feature data; storing, in an output file on one or more storage devices, the feature data and at least a subset of historical transactions; transmitting, from the one or more storage devices and over the computer network, the output file comprising the feature data for use in a machine learning application; and generating the machine learning algorithm for a machine learning model based on parameters in the output file, wherein the output file is configured to be transferred between at least two machine learning models. Other embodiments are described.
