biswajitsahoo1111/rul_codes_open

Implements reproducible RUL prediction pipelines on publicly available condition monitoring datasets with standardized evaluation metrics and benchmarking across multiple ML techniques. Emphasizes transparent methodology through documented code examples that demonstrate how feature engineering, model selection, and performance assessment apply to predictive maintenance workflows. Designed as a reference implementation for comparing algorithm effectiveness on real-world degradation data rather than synthetic benchmarks.

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