With the 2024 summer Olympics recently concluded and a lull in the early weeks of the fall semester, I decided to use a free weekend to act on a question I've been wondering: what would be the ideal Olympic event for my body?

What I wanted was to train a machine learning model to take in some basic biometrics, such as height and weight, and output an Olympic sport best for that person. Additionally, I wanted this project to be published online and easily accessible via a custom domain. Why? This project tackles a question I've been curious about, yes, but really I just wanted to practice doing something I've never done before: integrating a custom-trained machine learning model into a React web-app and hosting the model on an online server.

To train the model, I used this pre-compiled dataset from kaggle with basic bio data on Olympian athletes from the past 120 years. Using the tensorflow library, I defined a simple feedforward neural network that I trained using the dataset and exported the final model. The model itself during training wasn't the most accurate, especially because I chose the output feature to be specific events instead of sport categories (e.g. Men's 1500m instead of just "track and field"). However, the model is fine for my use case because even if the prediction isn’t perfect, it's likely still assigning a person to an event that fits someone with a similar body type or demographic. The model's predictions are more of a fun or exploratory tool rather than something life-changing or mission-critical, so it's more of a starting point for further exploration, not a final answer.