This repository contains predictive ml model

An ensemble of machine learning models for detecting fraudulent credit card transactions, utilizing advanced techniques for feature selection, data imbalance handling, and hyperparameter tuning.

Python app for detecting credit card frauds using a graph database

Detect Credit Card Fraud with Machine Learning in R

Data Analytics and Predictive Models for the Default of Credit Card Clients dataset by UC Irvine

The official JS library of Greip

CODSOFT Machine Learning Internship Tasks

Credit Card Fraud Detection using Logistic Regression algorithm

Anonymized credit card transactions labeled as fraudulent or genuine

Fraud Detection model based on anonymized credit card transactions

Credit card fraud detection

Credit Card and Debit Card Fraud Detection

This code snippet performs fraud detection using machine learning models such as RandomForestClassifier and DecisionTreeClassifier.

This project aims to detect credit card fraud by conducting exploratory data analysis (EDA), visualizing the data and applying various predictive models.

Machine Learning for Credit Card Fraud Detection

Data-Driven ML Credit Card Fraud Detection

The project is to build a fraud detection model using the dataset that has been provided and in doing so, increase revenue from transaction fees.

A curated list of data mining papers about fraud detection.

The increase in credit card fraud brought on by weaknesses in the system. We employ machine learning algorithms such as Logistic Regression, Decision Trees and Support Vector Machine. The accuracy results in detecting fraudulent transactions appears promising.