The goal of this project is to build site that can classify disaster messages and help emergancy forces to better alocate resources. The project uses figure 8 data to train a model that help identify messages as soon once the user enters it.

• Python
• sys
• pandas
• numpy
• NLTK
• sklearn
• html.parser
• plotly
• flask
• sqlalchemy

• Python 3.5+
• Machine Learning Libraries: NumPy, SciPy, Pandas, Sciki-Learn
• Natural Language Process Libraries: NLTK
• SQLlite Database Libraqries: SQLalchemy
• Model Loading and Saving Library: Pickle, joblib
• Web App and Data Visualization: Flask, Plotly

Installation

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/

The files are free to use

Project Link: https://github.com/Hangzoed/Disaster-Response-Pipeline

• Thanks for Firgure 8 for the Dataset
• Thanks for Udacity Data Science program for providing initial file structure page layout and amazing mentors
• I learned alot from sarasun97
• README template from othneildrewl It helped me to accelrate the README