ndleah/disaster-response

⛰️ machine learning pipeline for disaster alert

Disaster Response Pipeline Project

Introduction

This project will include a web app where an emergency worker can input a new message and get classification results in several categories. The web app will also display visualizations of the data.

⚙️ 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. Go to app directory: cd app

3. Run your web app: python run.py

4. Click the PREVIEW button to open the homepage

🚧 Folder Structure

- app
| - template
| |- master.html  # main page of web app
| |- go.html  # classification result page of web app
|- run.py  # Flask file that runs app

- data
|- disaster_categories.csv  # data to process 
|- disaster_messages.csv  # data to process
|- process_data.py
|- InsertDatabaseName.db   # database to save clean data to

- models
|- train_classifier.py
|- classifier.pkl  # saved model 

- README.md

📝 Feedback

If you have any feedback or ideas to improve this project, feel free to contact me via my email at nduongthucanh@gmail.com or:

---

© 2024 Leah Nguyen