Analyzed data set containing real messages that were sent during the disaster events from Appen (formally Figure 8). Created a machine learning pipeline to categorize these events.
The project includes a web app where an emergency message can be inputted and shows the classification results in several categories. The web app also displays visualizations of the data.
You can create a virtual environment by running python -m virtualenv venv and then activate.
You can install the necessary packages by running pip install -r requirements.txt
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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
- To run ETL pipeline that cleans data and stores in database
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Run the following command in the app's directory to run your web app.
python run.py -
Go to http://0.0.0.0:3000/