The aim of the case study is to build a multiple linear regression model for the prediction of demand for shared bikes.
- 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.
- 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.
- Based on various meteorological surveys and people's styles, the service provider firm has gathered a large dataset on daily bike demands across the American market based on some factors.
- Python - version 3.11.7
- Numpy - version 1.26.4
- Pandas - version 2.1.4
- Matplotlib - version 3.8.0
- Seaborn - version 0.12.2
- Statsmodels
- Sklearn
Give credit here.
- This project was based on learnings from updGrad course on Multiple Linear regression and EDA.
Created by [@Saket89] - feel free to contact me!