Disaster Response Pipeline Project

Project Overview:

This project is part of the Data Science Nanodegree Program by Udacity. The goal of this project is to analyze disaster data from Figure Eight to build a model for an API that classifies disaster messages.

Project Components:

1. ETL Pipeline:

   • Loads the messages and categories datasets
   • Merges the two datasets
   • Cleans the data
   • Stores it in a SQLite database

2. ML Pipeline:

   • Loads data from the SQLite database
   • Splits the dataset into training and test sets
   • Builds a text processing and machine learning pipeline
   • Trains and tunes a model using GridSearchCV
   • Outputs the results on the test set
   • Exports the final model as a pickle file

3. Flask Web App:

   • Data visualization using Plotly
   • Classify messages in real-time

File Structure:

• app
  • template
    • master.html # main page of web app
    • go.html # classification result page of web app
  • run.py # Flask file that runs the app
• data
  • disaster_categories.csv # data to process
  • disaster_messages.csv # data to process
  • process_data.py
  • DisasterResponse.db # database to save clean data to
• models
  • train_classifier.py
  • classifier.pkl # saved model
• README.md

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/

Screenshots:

1. Home Page:

2. Message Classification:

Acknowledgements:

• Udacity
• Figure Eight
• Stack Overflow
• Flask
• Plotly
• Scikit-learn
• SQLite
• Pandas
• NumPy
• NLTK
• SQLAlchemy
• Joblib
• Matplotlib
• Seaborn
• Pickle
• Jupyter Notebook
• Python
• HTML
• CSS
• JavaScript
• Bootstrap

License:

This project is licensed under the MIT License - see the LICENSE file for details.

Credits:

An Dinh Ngoc - andythetechnerd03