Bike Sharing Assignment

This is an assignment wherein a multiple linear regression model is built to predict demand for shared bikes depending on the current trend.

Table of Contents

• General Info
• Steps
• Technologies Used
• Conclusions
• Acknowledgements

General Information

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.

In such an attempt, BoomBikes aspires to understand the demand for shared bikes among the people after this ongoing quarantine situation ends across the nation due to Covid-19. They have planned this to prepare themselves to cater to the people's needs once the situation gets better all around and stand out from other service providers and make huge profits.

They have contracted a consulting company to understand the factors on which the demand for these shared bikes depends. Specifically, they want to understand the factors affecting the demand for these shared bikes in the American market. The company wants to know:

• Which variables are significant in predicting the demand for shared bikes.
• How well those variables describe the bike demands

Business Goal:

You 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.

Steps

1. Data Understanding
2. Data Cleaning and Preparation
3. Model building
4. Model Evaluation
5. Results

Conclusions

We are able to generate the linear regression model with R-squared value 0.801 to predict the bike sharing behaviour

Technologies Used

• Python 3.*
• Pandas
• NumPy
• SeaBorn
• MatPlotLib
• SkLearn
• StatsModels

Acknowledgements

We implemented this project as part of the Machine Learning 1 Module required for Post Graduate Diploma in Machine Learning and AI - IIIT,Bangalore (April -2022 batch).

• This project was based on this tutorial.

Contact

Created by Vishvmitra Belsare[@vishvmitra] - feel free to contact us!