LetsPopIn.com aims to enhance user experience by implementing an AI-based event matching system for users to events and with other users at that event. The current challenge is to efficiently connect users with events that align with their interests and preferences and matching them with others present. The goal of this project is to develop a prototype algorithm that can analyze user data and event characteristics to provide personalized event recommendations.

This will involve understanding user behavior, preferences, and historical data to create a model that predicts the best event matches. The project will allow learners to apply their knowledge of machine learning, data analysis, and algorithm development. The tasks will include data collection, feature engineering, model training, and evaluation. The project is designed to be completed by a team of learners specializing in data science or computer science within a single academic program.

The deliverables for this project include a functional prototype of the AI-based event matching algorithm, a comprehensive report detailing the methodology and findings, and a presentation of the results. The prototype should be able to process sample user data and provide event recommendations. The report should include data analysis, model development, and evaluation metrics. The presentation should summarize the project outcomes and demonstrate the algorithm's effectiveness.