Found 82 repositories(showing 30)
Aasritha-26
This project focuses on detecting fraudulent online payment transactions using machine learning, specifically leveraging a Random Forest Classifier enhanced with SMOTE (Synthetic Minority Over-sampling Technique) to handle class imbalance.
MandalaMukesh04
No description available
VYashasweeni
Machine Learning-based Online Payment Fraud Detection Web App built using Python, Scikit-learn, XGBoost, and Flask. The system analyzes transaction details like amount, type, and account balances to predict whether a transaction is fraudulent or legitimate, with real-time prediction through a user-friendly interface.
SKM2227229725
No description available
ankitsaini605
🛡️ Online Payment Fraud Detection System using Python, Pandas, Scikit‑Learn & ML models. 📊 Cleaned & processed transaction data, ⚡ applied classification algorithms, and 🎯 delivered accurate fraud detection insights to reduce financial risks & enhance payment security.
PrasadAjit
The "Online Payment Fraud Detection" project aims to identify and prevent fraudulent transactions in real-time. By leveraging machine learning models trained on historical transaction data, the system can distinguish between legitimate and suspicious activities.
23MH1A05F1
No description available
Dataset Description The dataset used for this project is the Credit Card Fraud Detection dataset available on Kaggle. outcome: Showed correct classification of most transactions. - Accuracy: ~99%
NukaThanuja
Mini-Project
This is a web application created using: Python and ML Concepts. The main aim of this system is identify the real time fraudulent transactions and report them.
Abdullah-Al-Mahamud
This project presents a machine learning–based classification system to detect fraudulent transactions in online payments. It leverages multiple classification algorithms and preprocessing techniques to train accurate fraud detection models.
aryadityad
🔍 Online Payments Fraud Detection using Machine Learning An end-to-end ML project that detects fraudulent transactions using real-world payment data. Features a high-performance XGBoost classifier, and a Flask-powered web app for real-time fraud prediction. Fully modular, scalable, and built for production-ready deployment.
Jahnavi-polukonda
“AI/ML-based system for online payment fraud detection using transaction data. Handles imbalanced datasets with SMOTE and advanced models (Logistic Regression, Random Forest, XGBoost). Includes preprocessing, EDA, training, and deployment-ready app with real-time fraud prediction and insights.”
chandureddy19
No description available
AshishSahani0
No description available
deepanshudg45
Online payment fraud detection using ML
kotapavithra
online payment fraud detection using ML
Saurav9937
Online Payment Fraud Detection Using ML
SwagathNalla
Online Payments Fraud Detection Using Ml
Harshitha284
Online Payment Fraud Detection Using ML
DivyaIngale11
Create Simple Ml Model
Amit-Sahu-data
No description available
sravanireddy18
This repository contains the implementation of a machine learning model using a Decision Tree Classifier. The model predicts outcomes based on a given dataset and demonstrates data preprocessing, training, and evaluation.
GarapatiVidyaSri
No description available
vijaykonidana28
It is project done for the internship by the SmartBridge.
No description available
Thanooj3034
No description available
Chaitanya-monk
This project uses machine learning techniques to detect fraudulent transactions in online payments. It involves data preprocessing, feature engineering, and model training using classification algorithms to identify suspicious activities. It is created using Jupyter
No description available
Gousebasha49
No description available