The main goal of this project is to develop a personalized events recommender system that suggests events to users based on their preferences and behaviors, using aggregated event data. This involves building a recommendation algorithm, integrating it with an event aggregator platform, and designing an engaging user interface to display the recommendations, ultimately enhancing user engagement with the platform.

Deliverables:

Student will be expected to work on and complete one part of the project:

Part 1:

1. Data Preparation: Cleaned and structured event dataset for use in the recommender system.

Part 2:

1. A basic functional 'proof of concept' recommender system integrated with the events platform.

Part 3:

1. Basic functional 'proof of concept' user interface for displaying the personalized event recommendations.

All students will be responsible for documentation of the recommendation algorithm, data preprocessing steps, and system integration