Disaster Response Pipeline Project

This Project is part of Udacity's Data Science Nanodegree in collaboration with Figure Eight. The initial dataset contains pre-labelled tweet and messages from real-life disaster. The aim of the project is to build a Natural Language Processing tool that categorize messages.

The Project is divided in the following Sections:

Data Processing, ETL Pipeline to extract data from source, clean data and save them in a proper databse structure Machine Learning Pipeline to train a model able to classify text message in categories Web App to show model results in real time.

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/

Project depenencies:

Python 3.5+ NumPy SciPy Pandas Scikit-Learn NLTK SQLalchemy Flask Plotly