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.