A web app to help emergency response to disaster. Based on ML methods, it classify the disaster data from Appen into different event categories, and send the messages to an appropriate disaster relief agency.
Install the python libraries defined in requirements.txt
pip install -r requirements.txt
Run the following commands in the project's root directory to set up the database, train and save model, finally run the web app
Step 1: 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
Step 2: to run ML pipeline that trains classifier and saves. If you want to try different ML algorithms and tune the model to get higher accuracy, then add --tunning as agurunment to following command line.
python models/train_classifier.py --database_filepath data/DisasterResponse.db --model_filepath models/classifier.pkl
Step 3: to run the web app
python app/run.py
Step 4: go to https://127.0.0.1:3001/
. ├── app │ ├── run.py │ └── templates │ ├──go.html │ └── master.html ├── data │ ├── DisasterResponse.db │ ├── disaster_categories.csv │ ├── disaster_messages.csv │ └── process_data.py ├── models │ └── train_classifier.py ├── .gitignore ├── README.md ├── poetry.lock └── pyproject.toml