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.
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Updated
Aug 5, 2024 - 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.
Machine Learning for Credit Card Fraud Detection
Credit Card Fraud Detection using ML
the application of an intelligence system to classify and identify fraud situations.
It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase.
Data Science Internship at CodSoft
Use of different classification models to detect credit card frauds
This project uses logistic regression models to analyze credit risk. The recommended model, trained with resampled data, shows higher precision and recall scores for predicting high-risk loans. This model helps mitigate credit risk for lending companies.
Titanic Survival Prediction, Movie Rating Prediction With Python, Iris Flower Classification, Sales Prediction Using Python, Credit Card Fraud Detection
In this Upgrad/IIIT-B Capstone project, we navigated the complex landscape of credit card fraud, employing advanced machine learning techniques to bolster banks against financial losses. With a focus on precision, we predicted fraudulent credit card transactions by analyzing customer-level data from Worldline and the Machine Learning Group.
This repository contains all my Machine Learning projects.
Classifying fraudulent transactions using K-Means SMOTE and ANN
This Python script uses machine learning models to detect fraudulent credit card transactions in a dataset. The dataset is loaded using the pandas library and preprocessed for machine learning by removing irrelevant features and rescaling the data.
Credit Card Fraud Detection is a crucial machine learning project with profound implications. It aims to safeguard financial transactions by identifying fraudulent activities. Leveraging advanced algorithms and historical transaction data, this project analyzes patterns and anomalies in credit card usage.
Implementation of an intelligence system to detect the fraud cases on the basis of classification.
Credit-Card-Fraud-Detection-System - 6th Semester College Project
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.
The objective of this project is to develop and utilize autoencoders for detecting anomalies in credit card transactions.
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