Disaster Response Pipeline Project

Create a machine learning pipeline to categorize real messages send during disaster events. Pipeline is used to categorize these events so that messages can be sent to an appropriate disaster relief agency. This project includes a web app where an emergency worker can input a new message and get classification results in several categories. The web app will aso display visualizations of the data.

Table of Contents

1. Quick start
2. What's included
3. Licensing, Authors, and Acknowledgements

1. Quick start

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1.1. 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`

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

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

2. What's included

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Disaster-Response-Pipelines/
└──.gitignore
├── app/
│   ├── run.py
│   └── templates/
│       ├── go.html
│       └── master.html
├── data/
│   ├── disaster_categories.csv
│   ├── disaster_messages.csv
│   ├── DisasterResponse.db
│   └── process_data.py
├── LICENSE
├── models/
│   └── train_classifier.py
├── README.md
└── utilities/
    └── print_file_structure.py

3. Licensing, Authors, and Acknowledgements

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Must give credit to Figure-eight for the data and Udacity for creating a beautiful learning experience.
Find the Licensing for the data and other descriptive information from Figure-eight.