Project Name

BoomBikes Linear Regression Assignment

Table of Contents

• Overview
• Understanding and scope of the assignment
• Analysis
• Preliminary observation and recommendation

General Information

• BoomBikes aspires to understand the demand for shared bikes among the people. The company wants to know: • Which variables are significant in predicting the demand for shared bikes. • How well those variables describe the bike demands 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, which can be accordingly manipulated for the business strategy to meet the demand levels and meet the customer's expectations.

Conclusions

• Please see the notebook

Technologies Used

• numpy
• pandas
• seaborn
• matplotlib
• sklearn
• statsmodels.api
• statsmodels.stats.outliers_influence

Acknowledgements

Give credit here.

• Use of this dataset in publications must be cited to the following publication:

[1] Fanaee-T, Hadi, and Gama, Joao, "Event labeling combining ensemble detectors and background knowledge", Progress in Artificial Intelligence (2013): pp. 1-15, Springer Berlin Heidelberg, doi:10.1007/s13748-013-0040-3.

@article{ year={2013}, issn={2192-6352}, journal={Progress in Artificial Intelligence}, doi={10.1007/s13748-013-0040-3}, title={Event labeling combining ensemble detectors and background knowledge}, url={http://dx.doi.org/10.1007/s13748-013-0040-3}, publisher={Springer Berlin Heidelberg}, keywords={Event labeling; Event detection; Ensemble learning; Background knowledge}, author={Fanaee-T, Hadi and Gama, Joao}, pages={1-15} }

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