In this project, our team used machine learning models in Python to see trends in healthy foods and unhealthy ones. We compiled a dataset, containing 17 different types of nutrients and labelled them as healthy or unhealthy. Then we ran machine learning algorithms to see if it could predict foods as healthy or unhealthy and assessed the trends it used to predict them such as the feature importance. We also analyzed trends within the data itself such as the correlation between 2 different nutrients.
Researchers
Atharva Patel, Lahari Karmuchi, Serena Chen
Advisor
Suresh Subramaniam
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