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1. Predicting-Bike-Rentals Predicting-Bike-Rentals Public

   This project predicts daily bike rental counts using weather and temporal features. Models include linear regression, KNN, random forest, and gradient boosting, all implemented in R with cross-vali…

   R

2. CounterfeitBills CounterfeitBills Public

   This project uses a Convolutional Neural Network (CNN) to detect counterfeit Egyptian pound bills and classify their denominations. By training on image data of bills (with and without the security…

   Python 1 1

3. Tsunami-Prediction-Using-Earthquake-Data Tsunami-Prediction-Using-Earthquake-Data Public

   This project uses the Global Earthquake-Tsunami Risk Assessment Dataset (782 quakes, 2001–2022) to predict tsunami occurrence. Four models—Logistic Regression, Random Forest, Gradient Boosting, and…

   Jupyter Notebook