
Create an ML system to forecast event attendance based on historical data, registration trends, and social media interest, helping organizers plan resources and logistics efficiently.
Collect historical attendance, registration data, and social media mentions for past events.
Design databases to store event details, participant data, and ML predictions.
Implement ML models for forecasting attendance using regression or time-series analysis.
Develop frontend dashboards displaying predicted vs. actual attendance, trends, and recommendations.
Integrate backend services for real-time updates, data processing, and notifications.
Test model accuracy, system performance, and dashboard usability.
Deploy on cloud servers for scalable predictions across multiple events.
Document ML methodology, prediction evaluation, and system implementation details.