Build a multiple linear regression model for the prediction of demand for shared bikes.

• General Info
• Technologies Used
• Conclusions

A bike-sharing system is a service in which bikes are made available for shared use to individuals on a short term basis for a price or free. Many bike share systems allow people to borrow a bike from a "dock" which is usually computer-controlled wherein the user enters the payment information, and the system unlocks it. This bike can then be returned to another dock belonging to the same system.

What is the background of your project?

A US bike-sharing provider BoomBikes has recently suffered considerable dips in their revenues due to the ongoing Corona pandemic. The company is finding it very difficult to sustain in the current market scenario. So, it has decided to come up with a mindful business plan to be able to accelerate its revenue as soon as the ongoing lockdown comes to an end, and the economy restores to a healthy state.

What is the business probem that your project is trying to solve?

We are required to model the demand for shared bikes with the available independent variables. It will be used by the management to understand how exactly the demands vary with different features. They can accordingly manipulate the business strategy to meet the demand levels and meet the customer's expectations. Further, the model will be a good way for management to understand the demand dynamics of a new market.

• Bike usage is significantly higher weather is Clear, Few clouds, partly cloudy, partly cloudy
• Bike demand takes a dip in Spring
• Bike demand doesn’t change whether day is working day or not.
• Bike demand in year 2019 is higher as compared to 2018. Bike demand is high in the months from May to October.
• The demand of bike is almost similar throughout the weekdays.

• Pandas
• Numpy
• Sci-kit Learn
• Statsmodels
• Seaborn
• Matplotlib

Created by [@Meghana-05] - feel free to contact me!