I built this project as part of my learning journey to explore how machine learning can be applied to personal finance. The idea was to create a simple application that helps users record their daily expenses, understand their spending habits, and get basic expense predictions using past transaction data. This project gave me hands-on experience with Python, Streamlit, data preprocessing, and integrating a machine learning model into a working application.
- Record daily transactions
- View transaction history
- Analyze spending patterns
- Expense prediction using machine learning
- Interactive charts and visualizations
- Generate financial reports
- Python
- Streamlit
- Pandas
- NumPy
- Scikit-learn
- Matplotlib
- Joblib
- Clone or download this repository.
- Install the required libraries: pip install -r requirements.txt
- Run the application: streamlit run app.py
Building this project helped me understand how machine learning models can be integrated into a real application. I also improved my understanding of data handling, model integration, and creating interactive dashboards with Streamlit.
- Add user authentication
- Improve prediction accuracy
- Connect to a cloud database
- Add budget planning and reminders
Sakshi Yadav B.Tech CSE (3rd Year)