公开(公告)号：US20200311617A1

公开(公告)日：2020-10-01

申请号：US16001548

申请日：2018-06-06

Applicant: Amazon Technologies, Inc.

Inventor： Charles Drummond SWAN ,  Edo LIBERTY ,  Steven Andrew LOEPPKY ,  Stefano STEFANI ,  Alexander Johannes SMOLA ,  Swaminathan SIVASUBRAMANIAN ,  Craig WILEY ,  Richard Shawn BICE ,  Thomas Albert FAULHABER, JR. ,  Taylor GOODHART

IPC: G06N99/00 ,  G06F9/455

Abstract: Techniques for using scoring algorithms utilizing containers for flexible machine learning inference are described. In some embodiments, a request to host a machine learning (ML) model within a service provider network on behalf of a user is received, the request identifying an endpoint to perform scoring using the ML model. An endpoint is initialized as a container running on a virtual machine based on a container image and used to score data and return a result of said scoring to a user device.

公开(公告)号：US20190164080A1

公开(公告)日：2019-05-30

申请号：US15822061

申请日：2017-11-24

Applicant: Amazon Technologies, Inc.

Inventor： Stefano STEFANI ,  Steven Andrew LOEPPKY ,  Thomas Albert FAULHABER, JR. ,  Craig WILEY ,  Edo LIBERTY

IPC: G06N99/00 ,  G06F9/455

Abstract: Techniques for auto-scaling hosted machine learning models for production inference are described. A machine learning model can be deployed in a hosted environment such that the infrastructure supporting the machine learning model scales dynamically with demand so that performance is not impacted. The model can be auto-scaled using reactive techniques or predictive techniques.

公开(公告)号：US20190156247A1

公开(公告)日：2019-05-23

申请号：US15919628

申请日：2018-03-13

Applicant: Amazon Technologies, Inc.

Inventor： Thomas Albert FAULHABER, JR. ,  Edo LIBERTY ,  Stefano STEFANI ,  Zohar KARNIN ,  Craig WILEY ,  Steven Andrew LOEPPKY ,  Swaminathan SIVASUBRAMANIAN ,  Alexander Johannes SMOLA ,  Taylor GOODHART

IPC: G06N99/00 ,  G06N5/04

Abstract: Techniques for dynamic accuracy-based experimentation and deployment of machine learning (ML) models are described. Inference traffic flowing to ML models and the accuracy of the models is analyzed and used to ensure that better performing models are executed more often via model selection. A predictive component can evaluate which model is more likely to be accurate for certain input data elements. Ensemble techniques can combine inference results of multiple ML models to aim to achieve a better overall result than any individual model could on its own.

公开(公告)号：US20220129334A1

公开(公告)日：2022-04-28

申请号：US17572470

申请日：2022-01-10

Applicant: Amazon Technologies, Inc.

Inventor： Vineet KHARE ,  Alexander Johannes SMOLA ,  Craig WILEY

IPC: G06F9/54 ,  G06F9/50 ,  G06F9/455 ,  G06N20/00 ,  G06Q10/00

Abstract: Techniques for providing and servicing listed repository items such as algorithms, data, models, pipelines, and/or notebooks are described. In some examples, web services provider receives a request for a listed repository item from a requester, the request indicating at least a category of the repository item and each listing of a repository item includes an indication of a category that the listed repository item belongs to and a storage location of the listed repository item, determines a suggestion of at least one listed repository item based on the request, and provides the suggestion of the at least one listed repository item to the requester.

公开(公告)号：US20190278640A1

公开(公告)日：2019-09-12

申请号：US15919178

申请日：2018-03-12

Applicant: Amazon Technologies, Inc.

Inventor： Vineet KHARE ,  Alexander Johannes SMOLA ,  Craig WILEY

IPC: G06F9/54 ,  G06F9/50 ,  G06F9/455 ,  G06F15/18

Abstract: Techniques for providing and servicing listed repository items such as algorithms, data, models, pipelines, and/or notebooks are described. In some examples, web services provider receives a request for a listed repository item from a requester, the request indicating at least a category of the repository item and each listing of a repository item includes an indication of a category that the listed repository item belongs to and a storage location of the listed repository item, determines a suggestion of at least one listed repository item based on the request, and provides the suggestion of the at least one listed repository item to the requester.