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mining-industry

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A project finished 02-22-2026 as part of the TripleTen Data Science program using real-world data and mimicking real-world project requirements. Task was to build a machine learning model capable of predicting gold recovery rates from gold ore using over 80 parameters recorded in the factory, totaling >1.5 million entries. Final sMAPE was 0.286.

  • Updated Jul 10, 2026
  • Jupyter Notebook

ML model forecasting gold recovery rates from ore processing. Identifies unprofitable production runs by analyzing flotation parameters and metal concentrations at rougher and final stages, enabling mining companies to optimize resource allocation and improve extraction efficiency.

  • Updated Aug 13, 2025
  • Jupyter Notebook

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