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applied-ml

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AmirhosseinHonardoust / Car-Value-Decomposition-Theory

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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.

random-forest predictive-modeling sensitivity-analysis machine-learning-theory interpretable-ml explainable-ai model-interpretability economic-modeling feature-attribution applied-ml consumer-analytics value-decomposition data-science-methods transparent-ai pricing-intelligence automotive-analytics car-price-modeling ml-explainability automotive-ml explainable-pricing
  • Updated Dec 10, 2025
  • Python

711nishtha / financial-fraud-detection-app

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Experimental web application demonstrating how an offline-trained financial fraud detection model can be exposed through a web interface. Built with Flask and a pre-trained XGBoost model to showcase ML inference flow, feature engineering, and result communication — not a production fraud prevention system.

flask web-application fraud-detection machine-learning-demo applied-ml ml-systems model-inference
  • Updated Jan 24, 2026
  • HTML

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