This project is part of the Udacity Data Scientist Nanodegree. This project tackles the challenge of classifying disaster messages. By training a Natural Language Processing model on real disaster data, it empowers responders to quickly understand the nature of incoming messages and react effectively.
+---app
| \---templates
| <> go.html
| <> master.html
+---data
| categories.csv
| DisasterResponse.db
| messages.csv
| process_data.py
+---images
| classified_message.png
| homepage.png
| visualizations.png
\---models
| train_classifier.py
|---README.md
|---requirements.txt
Install the necessary libraries
pip install -r requirements.txt- 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/messages.csv data/categories.csv data/DisasterResponse.db
- Expected output:
Loading data...
MESSAGES: data/messages.csv
CATEGORIES: data/categories.csv
Cleaning data...
Saving data...
DATABASE: data/DisasterResponse.db
Cleaned data saved to database!
- To run ML pipeline that trains classifier and saves:
python models/train_classifier.py data/DisasterResponse.db models/classifier.pkl
- Expected output:
Best parameter...
{'clf__estimator__min_samples_split': 2, 'clf__estimator__n_estimators': 20}
...
Category: direct_report
precision recall f1-score support
0 0.85 0.98 0.91 4208
1 0.78 0.33 0.46 1036
accuracy 0.85 5244
macro avg 0.82 0.65 0.69 5244
weighted avg 0.84 0.85 0.82 5244
Accuracy: 0.8485888634630053
F1 score: 0.822509670332959
Precision: 0.8399912434285646
Recall: 0.8485888634630053
Saving model...
MODEL: models/classifier.pkl
Trained model saved!
-
Run your web app:
python app\run.py -
Open
http://127.0.0.1:3001/in your web browser.