Bike Sharing Demand Prediction ( Machine Learning Project)

Problem Description

Recently, renting bikes has been widely spread because of how easy the process became after Bike sharing systems were introduced. Through these systems, user is able to easily rent a bike from a particular position and return back at another position. This results in increase in the average number of rented bikes. The problem is to predict the total count of bikes rented during each hour, using only information available prior to the rental period.

Dataset

https://www.kaggle.com/competitions/bike-sharing-demand/data

Final Solution

  • Model used: XGBoost
  • Evaluation on test data: R-squared = 0.819206 & RMSE = 0.096741