For any bank or financial organization, credit card fraud detection is of utmost importance. We have to spot potential fraud so that consumers can not bill for goods that they haven’t purchased. The aim is, therefore, to create a classifier that indicates whether a requested transaction is a fraud.
About Credit Card Fraud Detection In this machine learning project, we solve the problem of detecting credit card fraud transactions using machine numpy, scikit learn, and few other python libraries. We overcome the problem by creating a binary classifier and experimenting with various machine learning techniques to see which fits better.
Credit Card Fraud Dataset The dataset consists of 31 parameters. Due to confidentiality issues, 28 of the features are the result of the PCA transformation. “Time’ and “Amount” are the only aspects that were not modified with PCA. Dataset : https://www.kaggle.com/datasets/mlg-ulb/creditcardfraud