This is the BussinessView System of BikeRentPrediction Project: Data processing and analysis part: https://github.com/KevinMedicine26/BikeRentPrediction_Data
Prediction UI + backend + demo
The Bike Rental Prediction System is a comprehensive application that predicts bicycle rental demand based on weather conditions, leveraging a pre-trained Random Forest model. The system provides resource management capabilities to optimize worker allocation and bike distribution based on predicted demand.
The application follows a classic client-server architecture:
- User Interface (Browser)
- React Frontend (localhost:3000)
- Python Flask API (localhost:5000)
- Pre-trained Random Forest Model (.pkl)
Note: As this is a demonstration application, data is not synchronized between different browsers or devices. In a production environment, this would be replaced with a database backend.