I worked on cleaning data and developing models on the German Statlog Credit Dataset with 3 collaborators for my CS375 class at NJIT. I specifically trained a Random Forest Classifier model to determine whether customers were credit-worthy or not.
I used libraries like Scikit-Learn, pandas, and matplotlib to train the model and visualize the data. The model achieved an accuracy of 81.5%.