Disaster-Response-Project

In the Project Workspace, you'll find a data set containing real messages that were sent during disaster events. I had created a machine learning pipeline to categorize these events so that you can send the messages 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 also displays 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/