MACHINE LEARNING SERVICE
First Claim
1. A system, comprising:
- one or more computing devices configured to;
receive, via a particular programmatic interface of a set of programmatic interfaces implemented at a network-accessible machine learning service of a provider network, a first request from a client to perform a particular operation associated with an instance of an entity type, wherein the entity type comprises one or more of;
(a) a data source to be used for a machine learning model, (b) a set of statistics to be computed from a particular data source, (c) a set of feature processing transformation operations to be performed on a specified data set, (d) a machine learning model employing a selected algorithm, (e) an alias associated with a machine learning model, or (f) a result of a particular machine learning model;
insert a job object corresponding to the first request in a job queue of the machine learning service;
provide an indication to the client that the first request has been accepted for execution;
determine, in accordance with a first workload distribution strategy identified for the first request, a first set of provider network resources to be used to perform the particular operation;
receive, prior to a completion of the particular operation indicated in the first request, a second request from the client to perform a second operation dependent on a result of the particular operation;
insert a second job object corresponding to the second request in the job queue, wherein the second job object includes an indication of a dependency of the second operation on a result of the particular operation;
prior to initiating execution of the second operation, provide a second indication to the client that the second request has been accepted for execution; and
in response to a determination that the particular operation has been completed successfully, schedule the second operation on a second set of provider network resources.
1 Assignment
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Accused Products
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.
97 Citations
22 Claims
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1. A system, comprising:
one or more computing devices configured to; receive, via a particular programmatic interface of a set of programmatic interfaces implemented at a network-accessible machine learning service of a provider network, a first request from a client to perform a particular operation associated with an instance of an entity type, wherein the entity type comprises one or more of;
(a) a data source to be used for a machine learning model, (b) a set of statistics to be computed from a particular data source, (c) a set of feature processing transformation operations to be performed on a specified data set, (d) a machine learning model employing a selected algorithm, (e) an alias associated with a machine learning model, or (f) a result of a particular machine learning model;insert a job object corresponding to the first request in a job queue of the machine learning service; provide an indication to the client that the first request has been accepted for execution; determine, in accordance with a first workload distribution strategy identified for the first request, a first set of provider network resources to be used to perform the particular operation; receive, prior to a completion of the particular operation indicated in the first request, a second request from the client to perform a second operation dependent on a result of the particular operation; insert a second job object corresponding to the second request in the job queue, wherein the second job object includes an indication of a dependency of the second operation on a result of the particular operation; prior to initiating execution of the second operation, provide a second indication to the client that the second request has been accepted for execution; and in response to a determination that the particular operation has been completed successfully, schedule the second operation on a second set of provider network resources. - View Dependent Claims (2, 3, 4, 5)
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6. A method, comprising:
performing, by one or more computing devices; receiving, via a particular programmatic interface of a set of programmatic interfaces implemented at a machine learning service, a first request from a client to perform a particular operation associated with an instance of an entity type, wherein the entity type comprises one or more of;
(a) a data source to be used for generating a machine learning model, (b) a set of feature processing transformation operations to be performed on a specified data set, (c) a machine learning model employing a selected algorithm, or (d) an alias associated with a machine learning model;inserting a job corresponding to the first request in a job queue of the machine learning service; receiving, prior to a completion of the particular operation indicated in the first request, a second request from the client to perform a second operation dependent on a result of the particular operation; inserting a second job object corresponding to the second request in the job queue, wherein the second job object includes an indication of a dependency of the second operation on a result of the particular operation; and in response to determining that the particular operation has been completed successfully, scheduling the second operation. - View Dependent Claims (7, 8, 9, 10, 11, 12, 13, 14, 15)
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16. A non-transitory computer-accessible storage medium storing program instructions that when executed on one or more processors:
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receive, via a particular programmatic interface of a set of programmatic interfaces implemented at a network-accessible machine learning service of a provider network, a first request from a client to perform a particular operation associated with an instance of an entity type, wherein the entity type comprises one or more of;
(a) a data source to be used for generating a machine learning model, (b) a set of statistics to be computed from a particular data source, (c) a machine learning model employing a selected algorithm, or (d) an alias associated with a machine learning model;insert a job corresponding to the first request in a job queue of the machine learning service; receive, prior to a completion of the particular operation indicated in the first request, a second request from the client to perform a second operation dependent on a result of the particular operation; and insert a second job object corresponding to the second request in the job queue, wherein the second job object includes an indication of a dependency of the second operation on a result of the particular operation. - View Dependent Claims (17, 18, 19, 20, 21, 22)
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Specification