Students: Daniela Grandon, Patricio Fibla, Tomas Muller, Ryan Keegan, Humna Awan
Mentor: Pavlos Protopapas
We carry out a multiclass classification problem for predicting loan status from a rich dataset, building a (mock) loan approval pre-check system for potential customers. We employ various data techniques (e.g., imputation, one-hot encoding) and test multiple ML algorithms (Random Forest, Supper Vector Machine, and k-Nearest Neighbors).
We presented our work to the cohort at the end of the School; see here for the presentation.