Disaster Response Pipeline Project

Part of Data Scientist Nanodegree (Udacity)

Aim:

Analyze disaster data to build a model for an API that classifies disaster messages.

Project Description:

I used a data set containing real messages that were sent during disaster events and then created a machine learning pipeline to categorize these events so that messages can be sent to an appropriate disaster relief agency.

The 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 also display visualizations of the data.

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/

Screenshots Web App

Example:

Visualizations of the data: