Author: Juan Carlos Ramirez Cano
Date: November 2021
Disclaimer: This solution is showcased to share my understanding of the problem and my own approach to it. This solution is not intended for any general application.
Our motivation in this project will be to examine different Machine Learning approaches using the German Credit Risk Dataset hosted on Kaggle and the UC Irvine Machine Learning Repository. Each entry represents an individual seeking credit. Every client has been classified as a good or bad credit risk according to the set of attributes (features). The goal of this part of the project is to train a Support Vector Machine classifier on this dataset to predict credit risk.