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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-validation and RMSE-based evaluation.
abdel-elkasaby/Predicting-Bike-Rentals
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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-validation and RMSE-based evaluation.
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