The Objective of this Project was to develop a web app where the emergency responders can infer from a help message the type of help that needs to be supplied. This project uses Natural Language Processing and trains a Random Forest Classifier to categorize messages.

GitHub Code

Disaster Response Pipeline Project

Aim:

The Objective of this Project was to develop a web app where emergency workers can infer from a help message the possible categories that a message belongs to… to be able to redirect necessary support as per “shelter”, “food” etc

Demo

Dependencies

Python 3 and the following Python libraries installed:

NumPy
Pandas
Matplotlib
Json
Plotly
Nltk
Flask
Sklearn
Sqlalchemy
Sys
Re
Pickle

Instructions to run:

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://0.0.0.0:3003/ with udacity spaceid and domian

Results:

I was able to train the model and deploy the model

Data Source:

Figure Eight API

Acknowlegements

Udacity for the project template and Figure Eight for the data