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Developing a credit card fraud detection system using decision trees and artificial neural networks - Project done as part of MSc Data Science and Analytics Curriculum

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MSc Project - Credit Card Fraud Detection System using Decision Tree and ANN

Overview:

This project aims to develop a credit card fraud detection system as part of my MSc project. Utilizing machine learning techniques such as Decision Trees and Artificial Neural Networks (ANN), the study focuses on detecting fraudulent activity in credit card transactions and evaluating the effectiveness of each algorithm for accuracy.


Objectives:

  1. Authenticate and verify credit card holder details, analyze usage patterns, and promptly identify suspicious activities through machine learning techniques.
  2. Mitigate fraud potential, minimize credit card system losses, and achieve high accuracy in fraud detection using Decision Tree and ANN models.
  3. Develop a robust training model capable of predicting multiple target variable classes through decision tree algorithms and learning techniques.

Data Source:

https://www.kaggle.com/datasets/dhanushnarayananr/credit-card-fraud/

This Dataset is sourced by an unnamed institute according to the Kaggle dataset author.

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Developing a credit card fraud detection system using decision trees and artificial neural networks - Project done as part of MSc Data Science and Analytics Curriculum

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