Disaster Response Pipeline

Machine Learning project aims to classify the messeges in case of disaster

Table of Content

1. Installation
2. Initialize
3. Motivation
4. LICENSE

Installation

Necessary libraries:
You should face no issue running the file using Anaconda3 distribution

Initialize

1. Clone the full repository
2. Run the data/process_data.py file to create the clean database*
3. Run the models/train_classifier.py script to create the new model*

• Notice*: These Python scripts should be able to run with additional arguments specifying the files used for the data and model.
  • i.e: python process_data.py disaster_messages.csv disaster_categories.csv DisasterResponse.db
  • i.e: python train_classifier.py ../data/DisasterResponse.db classifier.pkl
    
• Doing that you have made your trained model and you are ready to predict and visualize your data
  

To visualize your data:

4. Run the app/run.py script
5. Open http://0.0.0.0:3001/

Motivations

While disaster, you have no time to think where I should send my SOS message, so I made this project to predict based on real messages that were sent during past disaster events, the category of new messages. It is a machine learning pipeline to categorize these events so that you can send the messages to an appropriate disaster relief agency.

LICENSE

This project is Under GNU LICENSE