Multiple linear regression model for the prediction of demand for shared bikes.

• General Info
• Technologies Used
• Conclusions
• Acknowledgements

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.

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.

Goal : 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.

• March,April,May,June,August,September and October months have positive corelation with target vatiable ( cnt - count of total rental bikes ), meaning March,April,May,June,August,September and October months have greater demand of rental bikes. .
• Year 2019 more bike was rtented compared to 2018.
• On monday,in general, more bikes are rented.
• Shared bike demand is less in winter.
• Weather conditions ( Light Snow, Light Rain + Thunderstorm + Scattered clouds, Light Rain + Scattered clouds ) has adverse effect on number of bike rented.
• Holiday has a negative corelation with number of bike rented.

• Python - 3.9.12
• numpy - 1.21.5
• pandas - 1.4.2
• matplotlib
• seaborn - 0.11.2
• sklearn
• statsmodels.api

Give credit here.

• This project was inspired by upGrade AI & ML course case study

Created by @sandipanp - feel free to contact me!