M1.1.C Recommending Sports

This study focuses on creating a sport recommendation system designed to encourage physical activity by suggesting sports based on a user’s demographic details, personality traits, and personal preferences. The system, housed within a web application, utilizes supervised machine learning to provide personalized sport suggestions based on responses to specific questions. Despite issues with low correlation between recommended sports and collected data, the study provides a foundation for future work, emphasizing the need to collect more relevant data for improved sport recommendations.

Reflection

This project served as my initial introduction to recommender systems and their technical aspects. The course laid a solid foundation for my understanding of Artificial Intelligence and its various applications. It taught me the steps involved in data collection, processing, system design, and how to utilize this data in crafting a recommender system. This learning experience not only influenced my M2.1 project, where I employed workshop-gathered data to build my prototype, but also shaped my fundamental comprehension of recommender systems for my FMP. 

Course: DBM180 Designing with advanced artificial intelligence

Grade: 8

Expertise Areas: Creativity and Aesthetics, Math, Data and Computing