Analysing Adversarial Attacks on Tabular Data Classifiers
AUTHORS: Alberto Ameglio Enrico Di Stasio Gianluca Di Bella Cosimo Vergari
pip install -r requirements.txt
Analysis of german credit data Project purpose The german credit data contains financial and banking details of customers. The given dataset contains information about individuals who have applied for credit from a bank. Each entry in the dataset represents a person, and they are classified as either good or bad credit risks based on their attributes. The task involves predicting whether the customer will repay a credit.
The aim of the project was to perform exploratory data analysis of german credit data. The goal of the data exploration and preprocessing was to gain knowledge about the features that influence credit repayment.
Other files