Disaster Response Pipeline Project

This project is to classify disaster response messages through machine learning.

Content

• Data
  • process_data.py: reads in the data, cleans and stores it in a SQL database. Basic usage is python process_data.py MESSAGES_DATA CATEGORIES_DATA NAME_FOR_DATABASE
  • disaster_categories.csv and disaster_messages.csv (dataset)
  • DisasterResponse.db: created database from transformed and cleaned data.
• Models
  • train_classifier.py: includes the code necessary to load data, transform it using natural language processing, run a machine learning model using GridSearchCV and train it. Basic usage is python train_classifier.py DATABASE_DIRECTORY SAVENAME_FOR_MODEL
• App
  • run.py: Flask app and the user interface used to predict results and display them.
  • templates: folder containing the html templates

Example:

python process_data.py disaster_messages.csv disaster_categories.csv DisasterResponse.db

python train_classifier.py ../data/DisasterResponse.db classifier.pkl

python run.py

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About

This project was prepared as part of the Udacity Data Scientist nanodegree programme. The data was provided by Figure Eight.