Skip to content
Apply Data Engineering to Build ETL & NLP Machine Learning Pipelines and Create an App for Disaster Relief using Flask
Jupyter Notebook Python HTML
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.
ETL Pipeline Preparation.ipynb
ML Pipeline Preparation.ipynb

Disaster Response Pipeline with Figure Eight

Apply Data Engineering to Build ETL & NLP Pipelines and Create an App for Disaster Relief using Flask

In this project, I am applying Data Engineering & Data Science skills to analyze disaster data from Figure Eight to build a model for an API that classifies disaster messages.

The project contains data set containing real messages that were sent during disaster events. I am creating a machine learning pipeline to categorize these events so that it can be sent to an appropriate disaster relief agency.

Project includes a web app where an emergency worker can input a new message and get classification results in several categories. The web app displays visualizations of the data.

There are three components in this project.

  1. ETL Pipeline A Python script,, a data cleaning pipeline that:

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

  1. ML Pipeline A Python script,, a machine learning pipeline that:

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 results on the test set Exports the final model as a pickle file

  1. Flask Web App
You can’t perform that action at this time.