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class-balancing

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Machine learning project predicting bank term deposit subscriptions using customer demographics and campaign data. Features multiple ML models (Random Forest, Logistic Regression, Decision Tree), SMOTE for class balancing, and interactive Streamlit app for real-time predictions.

  • Updated Oct 29, 2024
  • Jupyter Notebook

Cyclist safety risk assessment application for Austin using Random Forest classification with SMOTE for class balancing. Interactive Streamlit web app predicts cycling incident severity based on time, location, and environmental conditions to promote safer cycling practices.

  • Updated Oct 3, 2024
  • Jupyter Notebook

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