This project classifies text messages using NLP preprocessing and Scikit-Learn ML Pipelines

The code is separated into 3 parts:

1. ETL Pipeline
   • (E) Load Data from CSV files, (T) Clean Data and (L) Save to Database
   • data/process_data.py
2. ML Pipeline
   • Preprocess input text using NLP techniques + Train MultiOutputClassifier
   • model/train_classifier.py
3. Web Application
   • Serve trained model in a Flask web application
   • app/run.py

1. 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
2. Run ML pipeline that trains classifier and saves python models/train_classifier.py data/DisasterResponse.db models/classifier.pkl
3. Run Flask Web App that serves the trained model: python app/run.py