ARTI 308 - Machine Learning Credit Card Fraud Detection
Student Name: Ali Mohammed Aljanabi Student ID: 2240005182 Email: 2240005182@iau.edu.sa Academic Year: 2025/2026 - 2nd Semester
ABOUT THIS REPOSITORY This repository contains all lab assignments for ARTI 308 - Machine Learning. Each lab demonstrates practical implementation of machine learning concepts using Python, with a focus on real-world datasets and industry-standard workflows.
All labs are completed using Google Colab and follow the course requirements.
LAB 2 - COMPLETED ✅ Credit Card Fraud Detection
Objective: Identify a machine learning problem, select an open dataset, load/inspect the data, and create a methodology diagram.
Dataset: Credit Card Fraud Detection - Kaggle/ULB
- Records: 284,807 transactions
- Features: 31 (Time, V1-V28, Amount, Class)
- Target: Class (0 = Legitimate, 1 = Fraud)
- Challenge: 0.1727% fraud rate (highly imbalanced)
ML Problem: Binary Classification
Files in Lab 2 Folder:
- ARTI308_Lab2_FraudDetection.ipynb - Jupyter Notebook with data inspection
- Methodology Diagram.png - ML workflow diagram
- Machine Learning Problem - Lab 2 summary and problem definition