Publication | Closed Access
Developments in MLflow
97
Citations
10
References
2020
Year
Unknown Venue
Software MaintenanceMl Code InstrumentationEngineeringMachine LearningMachine Learning ToolSoftware EngineeringSimulationSoftware AnalysisEmpirical Software Engineering ResearchData ScienceManagementSoftware EnvironmentSystems EngineeringData IntegrationSoftware PracticeModel RegistryModeling And SimulationStream ProcessingMl DevelopmentData FlowModel DeploymentComputer ScienceSoftware DesignScientific Workflow SystemProgram AnalysisSoftware TestingSystem SoftwareData Modeling
MLflow is a popular open source platform for managing ML development, including experiment tracking, reproducibility, and deployment. In this paper, we discuss user feedback collected since MLflow was launched in 2018, as well as three major features we have introduced in response to this feedback: a Model Registry for collaborative model management and review, tools for simplifying ML code instrumentation, and experiment analytics functions for extracting insights from millions of ML experiments.
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