Food Bank Classification with Machine Learning

The three of us classified 130 Virginia counties based on food bank and food insecurity data, including merging and cleaning datasets of over 100 features. We used dimensionality reduction, clustering, and a Deep Neural Net to achieve 100% accuracy on differentiating "food swamps", "food deserts", and "food oases". Our 12-week "ML4VA" competition culminated in this paper and presentation: check them out to see how we did it!