Bike sharing systems are a means of renting bicycles. The goal of the Bike Sharing Demand competition is to predict demand by combining historical usage patterns with weather data.
- Explored the effect of features on the bike rental count using line and point plots
- Tested a variety of Regression models, including Linear regression, Ridge regression, Random forest regression, KNN and XGBoost
- Optimized the performance of the best performing models using GridSearch CV
- Used a voting ensemble on the optimized models to boost model performance resulting in a top 5% score
