A credit card mass checker tool that could check a card's validity based on luhn algorithm.

This repository implements Pozzolo, et al., (2015)'s probability calibration for imbalanced data.

Credit Fraud Detection for the course project for the master's degree in Software and Systems Engineering.

This project researched the credit card transaction dataset and tried various machine learning classification models on the dataset to determine the best model that would flag suspicious activity more accurately.

To build a classification methodology to predict whether a costumer is going to default for a payment or not.

Nothing strengthens better your knowledge in Deep Learning than coding an actual model and application. Take the 5 week challenge with Robert, David and George and join us each Friday for a fun and engaging hands-on coding session using TensorFlow 🎉

Codes related to data warehousing and mining

Creditcard fraud detection: Handling imbalanced data using Machine Learning

An analysis for finding out best method for credit card fraud detection. It's an comparison between three different classifiers: ANN, KNN and Decision Trees.

The Charge Documentation

This mini project was part of the module "Introduction To Data Science And Artificial Intelligence" (SC1015)

The problem statement is to predict fraudulent credit card transactions with the help of machine learning models. In this project, we need to analyse customer-level data that has been collected and analysed during a research collaboration of Worldline and the Machine Learning Group.

Detecting credit card fraud detection. Selecting an optimum threshold with analysis of confusion matrix and ROC curce

🛡️ Welcome to our Credit Card Fraud Detection project! 💳 Harnessing the formidable prowess machine learning, we're steadfast in our mission to fortify your financial stronghold against deceitful adversaries. Join our crusade for financial resilience,Ensuring every transaction is securely monitored! 🔐💯

belajar machine learning

To detect Credit Card Fraud by using SVR, Isolation Forest and Local Outlier Factor.

Use of different classification models to detect credit card frauds

This is the source code for the Credit Card Fraud Detection Project in Machine Learning.