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applied-ml

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This article explores the theory behind explainable car pricing using value decomposition, showing how machine learning models can break a predicted price into intuitive components such as brand premium, age depreciation, mileage influence, condition effects, and transmission or fuel-type adjustments.

  • Updated Dec 10, 2025
  • Python

Applied ML system predicting urban accessibility across Barcelona using geospatial features, SMOTE and Random Forest. Built for inclusive mobility.

  • Updated Nov 28, 2025
  • Jupyter Notebook

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