2020 · 100 citations · 10 references
ComputingComputer ScienceData ScienceMachine LearningModel-based Systems EngineeringSoftware EngineeringData-flow AnalysisExperimentation PlatformsModel Repository ManagementModel-driven DevelopmentModel-driven Software EngineeringSoftware ModelingCode InstrumentationCode Review WorkflowsExperiment LoggingExperimentation PipelinesModel Execution EnginesModel Library ManagementUser FeedbackUser Feedback Management
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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TensorFlow: A system for large-scale machine learning
Martı́n Abadi, Paul Barham, Jianmin Chen et al. · arXiv (Cornell University) · 2016 · 8.8K citations · Full text
TensorFlow: a system for large-scale machine learning
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