/udacity-disaster-response-project

Primary LanguagePython

Disaster Response Pipeline Project

This is my “disaster response pipeline” project for the data scientist nanodegree.

Contents

  • The folder notebooks contains some exploratory scripts. See in particular notebooks/ML Pipeline Preparation.py, where a grid search is used to find good parameter for the model.

  • The folder data contains the original message dataset (message text and categories), as two separate CSV files. The script process_data.py transforms and saves this to a database file.

  • The folder models contains the script train_classifier.py to train the model.

  • The folder app contains the Flask webapp that categorizes new messages. It assumes the database file and model generated by the scripts mentioned above are in the out folder at the root of this repository.

Instructions

  1. Run the following commands in the project's root directory to set up your database and model.

    • To run ETL pipeline that cleans data and stores in database python data/process_data.py data/disaster_messages.csv data/disaster_categories.csv out/DisasterResponse.db
    • To run ML pipeline that trains classifier and saves python models/train_classifier.py data/DisasterResponse.db out/classifier.pkl

  2. Run the following command in the app's directory to run your web app. python run.py

  3. Go to http://0.0.0.0:3001/

Acknowledgments

The code in this repository is based on a template provided by Udacity. In particular, the web app is almost unmodified from their example.