Description:

The competition dataset is based on the 2016 NYC Yellow Cab trip record data made available in Big Query on Google Cloud Platform. The data was originally published by the NYC Taxi and Limousine Commission (TLC). The data was sampled and cleaned for the purposes of this playground competition. Based on individual trip attributes, participants should predict the duration of each trip in the test set.

The datset contains the following fields: id - a unique identifier for each trip vendor_id - a code indicating the provider associated with the trip record pickup_datetime - date and time when the meter was engaged dropoff_datetime - date and time when the meter was disengaged passenger_count - the number of passengers in the vehicle (driver entered value) pickup_longitude - the longitude where the meter was engaged pickup_latitude - the latitude where the meter was engaged dropoff_longitude - the longitude where the meter was disengaged dropoff_latitude - the latitude where the meter was disengaged store_and_fwd_flag - This flag indicates whether the trip record was held in vehicle memory before sending to the vendor because the vehicle did not have a connection to the server - Y=store and forward; N=not a store and forward trip trip_duration - duration of the trip in seconds

Acknowledgement:

The dataset is taken from Kaggle: https://www.kaggle.com/c/nyc-taxi-trip-duration/data

Objective:

• Understand the Dataset & cleanup (if required).
• Build Regression models to predict the duration of taxi trip.
• Also evaluate the models & compare thier respective scores like R2, RMSE, etc.!