MACHINE LEARNING SYSTEM INTERFACE
First Claim
1. A computer-implemented method, comprising:
- generating an experiment management interface to present previous workflows ran on a machine learning system;
receiving, via the experiment management interface and with the machine learning system, an experiment initialization command to create a new experiment associated with a new workflow, wherein the experiment initialization command includes a selection of an existing workflow in the machine learning system, wherein the existing workflow is represented by an interdependency graph of one or more data processing operators;
receiving one or more modifications to the existing workflow via the experiment management interface;
scheduling the new workflow based on the modifications to the existing workflow for execution by a dynamic pool of computing devices; and
generating a visualization to facilitate analysis of the new experiment based on an input schema or an output schema of the new workflow.
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Accused Products
Abstract
Some embodiments include an experiment management interface for a machine learning system. The experiment management interface can manage one or more workflow runs related to building or testing machine learning models. The experiment management interface can receive an experiment initialization command to create a new experiment associated with a new workflow. A workflow can be represented by an interdependency graph of one or more data processing operators. The experiment management interface enables definition of the new workflow from scratch or by cloning and modifying an existing workflow. The workflow can define a summary format for its inputs and outputs. In some embodiments, the experiment management interface can automatically generate a comparative visualization at the conclusion of running the new workflow based on an input schema or an output schema of the new workflow.
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Citations
20 Claims
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1. A computer-implemented method, comprising:
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generating an experiment management interface to present previous workflows ran on a machine learning system; receiving, via the experiment management interface and with the machine learning system, an experiment initialization command to create a new experiment associated with a new workflow, wherein the experiment initialization command includes a selection of an existing workflow in the machine learning system, wherein the existing workflow is represented by an interdependency graph of one or more data processing operators; receiving one or more modifications to the existing workflow via the experiment management interface; scheduling the new workflow based on the modifications to the existing workflow for execution by a dynamic pool of computing devices; and generating a visualization to facilitate analysis of the new experiment based on an input schema or an output schema of the new workflow. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A computer readable data memory storing computer-executable instructions that, when executed, cause a computer system to perform a computer-implemented method, the instructions comprising:
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instructions for generating an experiment management interface to facilitate machine learning experimentations in a machine learning system; instructions for registering an experiment with an experiment management engine of the machine learning system; instructions for receiving, via an integrated development environment of the experiment management interface, a workflow definition text that defines a new workflow, wherein the workflow definition text describes an interdependency graph of one or more data processing operators; instructions for compiling the new workflow for execution on a dynamic pool of computing devices; and instructions for generating a visualization schema to facilitate analysis of the experiment based on an input schema or an output schema of the new workflow. - View Dependent Claims (15, 16, 17)
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18. A computer system, comprising:
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an experiment repository configured to store machine learning experiments previously executed on a machine learning system; an experiment management engine configured to generate an experiment definition interface for defining a new experiment and at least an associated workflow and an experiment visualization interface for analyzing a result of the new experiment; an experiment scheduler engine configured to schedule execution of the experiment via a pool of computing devices and distributing one or more code packages to at least a subset of the pool of computing devices; and wherein the experiment definition interface enables an experimenter to register the new experiment with a machine learning system, wherein the new experiment is based on one of the previous machine learning experiments, wherein the previous machine learning experiment is associated with an existing workflow represented by an interdependency graph of one or more data processing operators; and wherein the experiment visualization interface generates a visualization image comparing a first resulting output of a comparable previous experiment and a second resulting output of running the new experiment according to a visualization schema based on an input schema or an output schema of the associated workflow. - View Dependent Claims (19, 20)
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Specification