The credit card fraud detection model employs a Random Forest Classifier, a robust ensemble learning technique. It analyzes various transaction features to accurately identify fraudulent activities, leveraging the collective decision-making of multiple decision trees to enhance detection accuracy and resilience against data imbalances.

Logistic Regression, Random Forest & K-means Clustering algorithms are used in this project

Credit card transactions fraud detection using classic algorithms

Used Gaussian Naive Bayes Classifier and XG Boost Classifier for Credit Card Fault 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.

Fraud Detection model based on anonymized credit card transactions based on Isolation Forest Algorithm and Local Outlier Factor

This project aims to detect credit card fraud using Anamoly detection techniques such as Isolation Forest and Local Outlier Factor algorithms.

🛡️ 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! 🔐💯

This Repo contains Code and DataSet used with Results findout. I have used Logisitic Regression with Regulariztion, Plotted Graphs for Classfication applied Newton-Raphson Method .

Machine Learning based Credit Card Fraud Detection

A repository containing all my tasks/projects during my internship at CognoRise Infotech

Fraud Detection model based on anonymized credit card transactions based on Isolation Forest Algorithm and Local Outlier Factor

Anomaly detection analysis project in a credit card fraud detection with real anonymous data info from Kaggle

Full Stack Credit Card Fraud Detection Using Machine Learning with Code and Documents Plus Youtube Explanation Video

CODSOFT Machine Learning Internship Tasks

This repository consists of assignments and Models trained on various ML, NLP, & Deep Learning Algorithms.

Utilizando algoritmos de classificação para criar um modelo preditivo que seja capaz de detectar fraudes de cartão de crédito.

Credit Card Fraud Detection using Logistic Regression

Applied undersampling and oversampling using SMOTE.

💳 Detectando transações fraudulentas em cartões de crédito com scikit-learn, utilizando modelos de classificação.