GhostB is a full-stack financial management web application that leverages machine learning to analyze spending behavior and encourage mindful budgeting. Unlike traditional budgeting apps, GhostB introduces a cognitive spending mechanism that inflates unnecessary expense charges to make users more aware of their spending habits, helping them save more effectively.

• Real-Time Expense Classification
• Cognitive Spending Mechanism
• Ghost Budget System
• Automated Savings Allocation
• Full-Stack Implementation

• Frontend: HTML, CSS, JavaScript
• Backend: FastAPI, SQLAlchemy, SQLite, Scikit-learn, Pydantic, Uvicorn

1. Create a codespace within GitHub
2. Type "pip install -r requirements.txt"
3. Then type "uvicorn main:app --host 0.0.0.0 --port 8000 --reload"
4. Then type localhost:3000 on your browser

1. Users enter an expense (date, type, and amount).
2. The ML model analyzes the expense and determines if it is necessary or unnecessary.
3. If unnecessary, the system inflates the charge by up to 60%, making the user more mindful of extra spending.
4. The extra "ghost budget" is saved, and users can claim it back or allocate it to savings.