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公开(公告)号：US10963810B2
公开(公告)日：2021-03-30
申请号：US14569458
申请日：2014-12-12
Applicant: Amazon Technologies, Inc.
Inventor： Leo Parker Dirac , Aleksandr Mikhaylovich Ingerman
IPC: G06N20/00
Abstract: At a machine learning service, a determination is made that an analysis to detect whether at least a portion of contents of one or more observation records of a first data set are duplicated in a second set of observation records is to be performed. A duplication metric is obtained, indicative of a non-zero probability that one or more observation records of the second set are duplicates of respective observation records of the first set. In response to determining that the duplication metric meets a threshold criterion, one or more responsive actions are initiated, such as the transmission of a notification to a client of the service.
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公开(公告)号：US09552553B1
公开(公告)日：2017-01-24
申请号：US13926565
申请日：2013-06-25
Applicant: Amazon Technologies, Inc.
CPC classification number: G06N99/005 , G06Q10/083 , G06Q30/0601 , G06Q30/0621
Abstract: Disclosed are various embodiments for an item preparation application. Business logic and machine learning may be applied to attributes of an item to generate a recommendation for item preparation prior to storage in a physical storage facility. The recommendation may indicate whether preparation is to be applied, or what type of preparation is required. A machine learning knowledge base may be updated based on feedback or overrides of recommendations.
Abstract translation: 公开了用于物品准备应用的各种实施例。 业务逻辑和机器学习可以应用于项目的属性，以在存储在物理存储设施中之前生成用于项目准备的建议。 该建议可能表明是否应用准备工作，还是需要什么样的准备工作。 可以基于反馈或覆盖推荐来更新机器学习知识库。
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公开(公告)号：US10713589B1
公开(公告)日：2020-07-14
申请号：US15060439
申请日：2016-03-03
Applicant: Amazon Technologies, Inc.
Inventor： Saman Zarandioon , Nicolle M. Correa , Leo Parker Dirac , Aleksandr Mikhaylovich Ingerman , Steven Andrew Loeppky , Robert Matthias Steele , Tianming Zheng
IPC: G06N20/00
Abstract: A determination that a machine learning data set is to be shuffled is made. Tokens corresponding to the individual observation records are generated based on respective identifiers of the records' storage objects and record key values. Respective representative values are derived from the tokens. The observation records are rearranged based on a result of sorting the representative values and provided to a shuffle result destination.
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公开(公告)号：US20200050968A1
公开(公告)日：2020-02-13
申请号：US16657886
申请日：2019-10-18
Applicant: Amazon Technologies, Inc.
Abstract: A first data set corresponding to an evaluation run of a model is generated at a machine learning service for display via an interactive interface. The data set includes a prediction quality metric. A target value of an interpretation threshold associated with the model is determined based on a detection of a particular client's interaction with the interface. An indication of a change to the prediction quality metric that results from the selection of the target value may be initiated.
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公开(公告)号：US20220391763A1
公开(公告)日：2022-12-08
申请号：US17811555
申请日：2022-07-08
Applicant: Amazon Technologies, Inc.
Inventor： Leo Parker Dirac , Nicolle M. Correa , Aleksandr Mikhaylovich Ingerman , Sriram Krishnan , Jin Li , Sudhakar Rao Puvvadi , Saman Zarandioon
IPC: G06N20/00
Abstract: A machine learning service implements programmatic interfaces for a variety of operations on several entity types, such as data sources, statistics, feature processing recipes, models, and aliases. A first request to perform an operation on an instance of a particular entity type is received, and a first job corresponding to the requested operation is inserted in a job queue. Prior to the completion of the first job, a second request to perform another operation is received, where the second operation depends on a result of the operation represented by the first job. A second job, indicating a dependency on the first job, is stored in the job queue. The second job is initiated when the first job completes.
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Patent Agency Ranking
公开(公告)号：US20190050756A1
公开(公告)日：2019-02-14
申请号：US16159441
申请日：2018-10-12
Applicant: Amazon Technologies, Inc.
Inventor： Leo Parker Dirac , Nicolle M. Correa , Aleksandr Mikhaylovich Ingerman , Sriram Krishnan , Jin Li , Sudhakar Rao Puvvadi , Saman Zarandioon
IPC: G06N99/00
Abstract: A machine learning service implements programmatic interfaces for a variety of operations on several entity types, such as data sources, statistics, feature processing recipes, models, and aliases. A first request to perform an operation on an instance of a particular entity type is received, and a first job corresponding to the requested operation is inserted in a job queue. Prior to the completion of the first job, a second request to perform another operation is received, where the second operation depends on a result of the operation represented by the first job. A second job, indicating a dependency on the first job, is stored in the job queue. The second job is initiated when the first job completes.
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公开(公告)号：US12073298B2
公开(公告)日：2024-08-27
申请号：US17811555
申请日：2022-07-08
Applicant: Amazon Technologies, Inc.
Inventor： Leo Parker Dirac , Nicolle M. Correa , Aleksandr Mikhaylovich Ingerman , Sriram Krishnan , Jin Li , Sudhakar Rao Puvvadi , Saman Zarandioon
IPC: G06N20/00
CPC classification number: G06N20/00
Abstract: A machine learning service implements programmatic interfaces for a variety of operations on several entity types, such as data sources, statistics, feature processing recipes, models, and aliases. A first request to perform an operation on an instance of a particular entity type is received, and a first job corresponding to the requested operation is inserted in a job queue. Prior to the completion of the first job, a second request to perform another operation is received, where the second operation depends on a result of the operation represented by the first job. A second job, indicating a dependency on the first job, is stored in the job queue. The second job is initiated when the first job completes.
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公开(公告)号：US10452992B2
公开(公告)日：2019-10-22
申请号：US14538723
申请日：2014-11-11
Applicant: Amazon Technologies, Inc.
Abstract: A first data set corresponding to an evaluation run of a model is generated at a machine learning service for display via an interactive interface. The data set includes a prediction quality metric. A target value of an interpretation threshold associated with the model is determined based on a detection of a particular client's interaction with the interface. An indication of a change to the prediction quality metric that results from the selection of the target value may be initiated.
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公开(公告)号：US10102480B2
公开(公告)日：2018-10-16
申请号：US14319902
申请日：2014-06-30
Applicant: Amazon technologies, Inc.
Inventor： Leo Parker Dirac , Nicolle M. Correa , Aleksandr Mikhaylovich Ingerman , Sriram Krishnan , Jin Li , Sudhakar Rao Puvvadi , Saman Zarandioon
IPC: G06N99/00
Abstract: A machine learning service implements programmatic interfaces for a variety of operations on several entity types, such as data sources, statistics, feature processing recipes, models, and aliases. A first request to perform an operation on an instance of a particular entity type is received, and a first job corresponding to the requested operation is inserted in a job queue. Prior to the completion of the first job, a second request to perform another operation is received, where the second operation depends on a result of the operation represented by the first job. A second job, indicating a dependency on the first job, is stored in the job queue. The second job is initiated when the first job completes.
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公开(公告)号：US12229642B2
公开(公告)日：2025-02-18
申请号：US17214047
申请日：2021-03-26
Applicant: Amazon Technologies, Inc.
Inventor： Leo Parker Dirac , Aleksandr Mikhaylovich Ingerman
IPC: G06N20/00
Abstract: At a machine learning service, a determination is made that an analysis to detect whether at least a portion of contents of one or more observation records of a first data set are duplicated in a second set of observation records is to be performed. A duplication metric is obtained, indicative of a non-zero probability that one or more observation records of the second set are duplicates of respective observation records of the first set. In response to determining that the duplication metric meets a threshold criterion, one or more responsive actions are initiated, such as the transmission of a notification to a client of the service.
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