Disaster Response Pipeline

This is a webapp that provides a visualization tool for categorizing a message in 36 different categories.

Background and motivation

This project is part of Udacity's Data Science nanodegree. It's purpose includes:

Cleaning and loading data gathered from two datasets and store it in a database, making it ready for use;
Build and train a Machine Learning model using Natural Language Process that is able to classify a message into 36 different categories;
Use this trained moded to classify a message inputed by user.

(this part of the text was extracted from the exercise)

Run the following commands in the project's root directory to set up 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 it to a model
```
python models/train_classifier.py data/DisasterResponse.db models/classifier.pkl
```
Run the following command in the app's directory to run the web app. python run.py
Go to http://0.0.0.0:3001/