Author Ibrahim Koné

New York City Taxi Fare Prediction Kaggle Web App

Download Dataset Here

Do you remember the days before Uber, Lyft, or Gett? Standing in the street trying to hail a taxi waiting for the moment a free cab might drive by and spot you? These days that world seems so far away. And you might often wonder: how do these apps work.

How to use it

$ # Get the code
$ git clone https://github.com/Ibmaria/New-York-City-Taxi-Fare-Prediction.git
$ cd New-York-City-Taxi-Fare-Prediction
$
$ # Virtualenv modules installation (Unix based systems)
$ virtualenv env
$ source env/bin/activate
$
$ # Virtualenv modules installation (Windows based systems)
$ # virtualenv env
$ # .\env\Scripts\activate
$
$ # Install modules - SQLite Storage
$ pip3 install -r requirements.txt or pip install -r requirements.txt
$
$ # Create tables
$ python manage.py makemigrations
$ python manage.py migrate
$
$ # Start the application (development mode)
$ python manage.py runserver # default port 8000
$
$ # Start the app - custom port
$ # python manage.py runserver 0.0.0.0:<your_port>
$
$ # Access the web app in browser: http://127.0.0.1:8000/projets/taxi/

App Screenshot

Download Video App Here

Codebase structure

The project is coded using a simple and intuitive structure presented below:

< PROJECT ROOT >
   |
   |-- taxi/                              
   |--taxidriver/
   |--Docker-version
   |--classify_image.py                        
   |--Dockerfile              
   |--requirements.txt
   |--manage.py
   |--pima_dataset_lgbm_final.txt
   |-- ************************************************************************