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Continuous background services that perform hyperparameter sampling independently of main execution scripts.
Distinct from Hyperparameter Optimization: Focuses on the architectural 'service' aspect (background, independent operation) rather than just the optimization algorithm.
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ClearML is a comprehensive MLOps platform designed to manage the end-to-end machine learning lifecycle, from initial experimentation to production deployment. It provides a suite of integrated tools including a pipeline orchestrator for automating workflows, an experiment tracking tool for logging hyperparameters and metrics, and a metadata-driven data versioning system for managing large-scale datasets and model artifacts. The platform is distinguished by its advanced compute management and serving capabilities. It features a GPU compute manager that supports fractional resource slicing and
Runs continuous background sampling services to find optimal model parameters independently of the main scripts.