foreXpert is a machine learning-powered web application for forecasting future exchange rates. Built with Python and Flask, the system combines statistical and ensemble learning models to generate future currency predictions. It features a fast, interactive, and intuitive user interface.
- Multiple forecasting models: Prophet, XGBoost, Random Forest, Linear Regression
- Automated feature engineering from historical exchange rate data
- Interactive interface built with Flask
- Visual comparison of actual vs. predicted performance
- Currency data fetched from public APIs
- Frontend: HTML5, CSS (served via Flask templates)
- Backend: Flask (Python)
- Models: Prophet, XGBoost, Scikit-learn
- Data Source: Public exchange rate APIs (e.g., exchangeratesapi)
- flask
- pandas
- numpy
- scikit-learn
- xgboost
- prophet
- requests
pip install -r requirements.txt
python app.py
Then open http://localhost:5000 in your browser to use the application.
- app.py: Main application file
- templates/: HTML templates
- static/: CSS or image files
- models/: Trained models
- requirements.txt: Required dependencies
- LICENSE: MIT license
- README.md: Project description
This project is licensed under the MIT License. It is open-source and free to use.
machine-learning, time-series, currency-forecasting, flask, python, prophet, xgboost, scikit-learn, forecasting-app