Open database for metallurgical & mining processes. Synthetic and official datasets for data science, ML, and Power BI. Includes Peruvian mining production data (MINEM 2021–2025).
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Updated
May 2, 2026 - Jupyter Notebook
Open database for metallurgical & mining processes. Synthetic and official datasets for data science, ML, and Power BI. Includes Peruvian mining production data (MINEM 2021–2025).
👷 Nornickel Hackathon Submission
Supervisory control and decoupled MIMO PID regulation for a pilot-scale copper flotation column using PLC, OPC, and industrial HMI.
After reading "Gaussian process regression for modeling computational and experimental mineral processing data" by Eskanlou et al. (Mineral-X, Stanford), I applied their GPR workflow to my own Cu-Mo plant flotation data and inverted it for the window that minimises Cu in the Mo concentrate.
Mineral process quality forecasting on Databricks — flotation plant ML platform with SPC charts, what-if simulator, and Medallion architecture. Real industrial data (737K rows, 24 sensors).
Sensor virtual de sílice en flotación de hierro con datos reales de planta: 3 filtraciones cerradas, persistencia como línea base, holdout abierto una vez y bootstrap por días.
ML pipeline for grade and recovery prediction in froth flotation. A UG2 platinum circuits and iron ore time-series forecasting
Planta de flotación real (Kaggle, mineral de hierro): qué se puede predecir de la sílice del concentrado y por qué los datos no permiten recetar setpoints de reactivos.
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