公开(公告)号：US11727314B2

公开(公告)日：2023-08-15

申请号：US16587301

申请日：2019-09-30

Applicant: Amazon Technologies, Inc.

Inventor： Tanya Bansal ,  Piali Das ,  Leo Parker Dirac ,  Fan Li ,  Zohar Karnin ,  Philip Gautier ,  Patricia Grao Gil ,  Laurence Louis Eric Rouesnel ,  Ravikumar Anantakrishnan Venkateswar ,  Orchid Majumder ,  Stefano Stefani ,  Vladimir Zhukov

IPC: G06N20/20 ,  G06F9/50 ,  G06F9/54

CPC classification number: G06N20/20 ,  G06F9/5066 ,  G06F9/546

Abstract: Techniques for automated machine learning (ML) pipeline exploration and deployment are described. An automated ML pipeline generation system allows users to easily construct optimized ML pipelines by providing a dataset, identifying a target column in the dataset, and providing an exploration budget. Multiple candidate ML pipelines can be identified and evaluated through an exploration process, and a best ML pipeline can be provided to the requesting user or deployed for production inference. Users can configure, monitor, and adapt the exploration at multiple points in time throughout.

公开(公告)号：US12061963B1

公开(公告)日：2024-08-13

申请号：US18340561

申请日：2023-06-23

Applicant: Amazon Technologies, Inc.

Inventor： Tanya Bansal ,  Piali Das ,  Leo Parker Dirac ,  Fan Li ,  Zohar Karnin ,  Philip Gautier ,  Patricia Grao Gil ,  Laurence Louis Eric Rouesnel ,  Ravikumar Anantakrishnan Venkateswar ,  Orchid Majumder ,  Stefano Stefani ,  Vladimir Zhukov

IPC: G06N20/20 ,  G06F9/50 ,  G06F9/54

CPC classification number: G06N20/20 ,  G06F9/5066 ,  G06F9/546

Abstract: Techniques for automated machine learning (ML) pipeline exploration and deployment are described. An automated ML pipeline generation system allows users to easily construct optimized ML pipelines by providing a dataset, identifying a target column in the dataset, and providing an exploration budget. Multiple candidate ML pipelines can be identified and evaluated through an exploration process, and a best ML pipeline can be provided to the requesting user or deployed for production inference. Users can configure, monitor, and adapt the exploration at multiple points in time throughout.