Implementation of an intelligence system to detect the fraud cases on the basis of classification.
credit-card fraud credit-card-fraud-detection creditcardfrauddetection frauddetection creditcard-csv
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- Python
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creditcardfrauddetection
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This repo contains 4 different projects. Built various machine learning models for Kaggle competitions. Also carried out Exploratory Data Analysis, Data Cleaning, Data Visualization, Data Munging, Feature Selection etc
data-science machine-learning exploratory-data-analysis kaggle kaggle-competition data-analysis house-price-prediction data-munging datavisualization datacleaning datamunging diabetes-prediction creditcardfrauddetection bankloanprediction
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Credit Card Fraud Prediction in ASP.NET Core using ML.NET
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Golang wrapper for Prompt API's BIN Checker API
golang credit-card api-wrapper golang-package creditcardfrauddetection promptapi bin-number bin-checker api-marketplace bincheck-api bin-lookup bin-database credit-card-bin binlookup
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- Ruby
This repository contains an implementation of credit card fault detection using Luhn's algorithm. Luhn's algorithm is a checksum formula used to validate credit card numbers, as well as other identification numbers. The algorithm is based on performing a set of arithmetic operations on the digits of a given number, resulting in a checksum value.
credit-card-fraud creditcard luhn-algorithm creditcard-validator luhn-checksum luhn-validation luhn-checkdigit creditcardfrauddetection creditcardfraud creditcardfault
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- Python
Creditcard validator by Using Luhn's algorithm to verify the validity of credit card numbers. It also fetches credit card number data from datasets for testing and analysis.
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- Python
A machine learning project to detect fraudulent credit card transactions using real-world data.
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This repository demonstrates how to build a robust fraud detection system that combines supervised learning techniques with anomaly detection models. It provides end-to-end implementation, from data preprocessing and model training to deploying a real-time fraud detection API using FastAPI.
python data machinelearning fraud-detection anomaly-detection supervised-machine-learning unsupervised-machine-learning dataanalytics fastapi creditcardfrauddetection modeldeployment
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This is a classification problem to detect or classify the fraud with label 0 or 1. Class with label 1 means fraud is detected otherwise 0. The biggest challenge is to handle the imbalanced data set.
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Ruby package for Prompt API's BIN Checker API
ruby credit-card api-wrapper creditcardfrauddetection promptapi bin-number bin-checker api-marketplace bincheck-api bin-lookup bin-database credit-card-bin
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- Ruby
Technocolabs Machine Learning Developer Internship Project 2
internship machine-learning-algorithms heroku-deployment creditcardfrauddetection streamlit technocolab
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Classifying fraudulent transactions using K-Means SMOTE and ANN
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This project aims at creating a classifier. It detects whether or not the card transaction is valid. Diverse machine learning algorithms are applied in this project to distinguish between a non-fraudulent and fraudulent transactions.
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Implementation of an intelligence system to detect the fraud cases on the basis of classification.
support-vector-machines pandas-library matplotlib-pyplot seaborn-plots creditcardfrauddetection decison-tree-regressor
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Credit card fraud detection using Random Forest — 99.96% accuracy.
python fintech randomforest classification machinelearning imbalanced-data creditcardfrauddetection frauddetection
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- Jupyter Notebook
Credit card fraud is a significant global issue, posing challenges for financial institutions due to the low incidence of fraud amid a high volume of legitimate transactions.
visualization data-science data machine-learning-algorithms credit-card feature-extraction credit-risk creditcardfrauddetection
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Machine Learning for Credit Card Fraud Detection
machine-learning machine-learning-algorithms credit-card-fraud neural-networks keras-tensorflow creditcardfrauddetection
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- Jupyter Notebook
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