Zestfinance, Inc.

Saar Yalov

Jerome Louis Budzik

Yunyan Zhang

Bingjia Wang

David Sheehan

Qiumeng Yu

Adam Kleinman

Ruochen Zha

Lingzhi Du

Sean Javad Kamkar

Siavash Yasini

Siavash Yasani

This application describes systems and methods for generating machine learning models (MLMs). An exemplary method includes obtaining a sample and user input data characterizing a product or service. A subset of the data is selected from the sample based on sampling the sample according to the user input data. An MLM is trained by applying the data subset as training input to the MLM, thereby providing a trained MLM to emulate a customer selection process unique to the product or service. A user interface (UI) configured to receive other user input data and cause the trained MLM to execute on the other user input data, thereby testing the trained MLM, is presented. A summary of results from the execution of the trained MLM is generated and presented in the UI. The summary of results indicates a contribution to the trained MLM of each of a plurality of features.

Automated systems for machine learning model development, analysis, and refinement

Growing community of inventors

Los Angeles, CA, United States of America

Saar Yalov