A streamlined Streamlit web app for tracking personal expenses with AI-powered automatic categorization. Generate sample data, train an ML model, and launch an interactive dashboard with insights and visualizations.
- AI Categorization: Predicts expense categories with ~85–95% accuracy
- Interactive Dashboard: Category breakdowns, trends, recent transactions
- AI Insights: Data-driven tips and category analysis
- Fast Add & Import: Manual entry or CSV bulk import
- Exportable Data: Download transactions and reports
- Python, Streamlit, Plotly, Pandas, scikit-learn
- TF-IDF text features + ML models (Naive Bayes, Logistic Regression, Random Forest)
From the expense-tracker/ folder:
pip install -r requirements.txt
python generate_data.py
python train_model.py
streamlit run app.pyThen open http://localhost:8501.
expense-tracker/— App source, data generation, model training, and docsREADME.md— Full documentation and usage guideGET_STARTED.md— Step-by-step setup guide
- Full docs:
expense-tracker/README.md - Getting started:
expense-tracker/GET_STARTED.md
MIT License.
Built with Streamlit, scikit-learn, Plotly, and Pandas.