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Disaster Response Pipeline Project

Summary:

This project is an analysis for messages that were sent during disasters. The goal is to create an ETL and a machine learning pipelines to classify the messages into pre-defined categories, to help emergency workers respond to them effectivly.

Files:

  • app
    • templates
      • go.html
      • master.html
    • run.py
  • data
    • disaster_categories.csv
    • disaster_messages.csv
    • process_data.py
  • models
    • train_classifier.py

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 data/DisasterResponse.db
    • To run ML pipeline that trains classifier and saves python models/train_classifier.py data/DisasterResponse.db models/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/

Attribution:

The data set used in this project was provided by Figure Eight.