Bike rentals have become very common in the Western world. A customer can simply rent a bike by the hour or day. The aim of this project is to analyze and predict the number of bike rentals recieved by the hour in Washington D.C. district. The analysis identifies the factors influencing bike rentals and finally using these factors, predicts the estimated bike rentals recieved per hour. The dataset can be found at the UCI machine learning repository - Link

The notebook contains detailed steps for the same with interactive visualizations. The visualizations made in plotly cannot be rendered on Github and hence it would be advisable to view it on this Link