Trip Duration Predictor

Setting Up the Conda Environment

Creating a New Conda Environment from environment.yml

To create a new Conda environment from the provided environment.yml file, run:

conda env create -f environment.yml

Overview

This project aims to predict the travel duration (in seconds) for ride-sharing trips based on ride start/end geospatial coordinates (WGS84) and the departure datetime. The model is evaluated using the Root Mean Squared Error (RMSE) metric.

Data Description

• train.csv: Contains ride details with columns:
  • row_id: Unique identifier for each trip
  • start_lng, start_lat: Longitude and latitude of the ride's starting location
  • end_lng, end_lat: Longitude and latitude of the ride's destination
  • datetime: Trip start time (local)
  • duration: Actual trip duration in seconds
• test.csv: Contains ride details for which predictions are to be made with columns:
  • row_id: Unique identifier for each trip
  • start_lng, start_lat: Longitude and latitude of the ride's starting location
  • end_lng, end_lat: Longitude and latitude of the ride's destination
  • datetime: Trip start time (local)