Disaster Response Pipeline Project

During a disaster the helping personnel receives lots of online text messages, but they have no time to analyse if they are relevant.

With this web app you may enter a text message and get indicated, what kind of message it is.

The classication model was trained on a dataset of more than 26000 real world text messages sent in a disaster context.

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/ Or if you are working in a udacity workspace environment: run app/app-url.sh and click on the displayed url