1.Purposes

The major objectives of our project were the regression and projections of bike riders at a certain Bay Area city for a specific day using the multiple time, weather, and behavior factors that we have access to.

In order to anticipate the travel patterns for certain cities using the processed data, we planned to examine the dataset, manipulate and extract the data, pre-process the dataset, and then use regression algorithms and approaches.

DataSet Link - https://www.kaggle.com/datasets/benhamner/sf-bay-area-bike-share?datasetId=57&sortBy=voteCount

2.Algorithms Selected to Train and Evaluate

1. RandomForestRegression
2. ExtraTreesRegression
3. XGBoostRegressor
4. KNNRegression
5. LassoRegression
6. GradientBoostingRegressor

3.Running and Comapring all Algorithms

Built With

• python