Amazon Technologies, Inc.

Hang Zhang

Alexander Johannes Smola

Mu Li

Nick Dean Erickson

Abhi Vinayaka Sharma

Tatsuya Arai

Ryan Matthew Brand

Jonas Mueller

Yohei Nakayama

Techniques for code-free automated machine learning (ML) are described. Users can train high-quality ML models and pipelines without necessarily needing to write code by providing a training dataset to a code-free machine learning service. The service may deploy an ML orchestration function and a storage location on behalf of a user. When a modification is made to the storage bucket, such as by the user providing a training dataset, the orchestration function is invoked and can automatically initiate an AutoML process using at least the training data to train multiple ML model variants. The resultant ML model(s) and associated metrics can be provided to the user, deployed behind an endpoint, and/or used to generate inferences.

Code-free automated machine learning

Growing community of inventors

San Carlos, CA, United States of America

Hang Zhang