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MLE Infrastructure provides a reproducible workflow for distributed Machine Learning experimentation with minimal engineering overhead. Its core consists of five standalone packages for experiment logging, hyperparameter optimization, resource monitoring, job scheduling, and experiment management.
AI named mle-scheduler in December 2025.