You are going to need pandas, numpy, matplotlib, imbalanced-learn, sklearn, and seaborn.
Simply run ClassificationModel.py and it will start bringing up visual graphs of the data preprocessing data as well as the final evaluation metrics for the Logistic Regression and Support Vector Classifier models. The outputs will also be printed to the console. Close each graph to move onto the next, keep note that after closing the LR graphs it will take about 5-10 seconds for the SVM to run and output a graph.