Building Credit Card Fraud Detection with Machine Learning

Below are things that you can expect to learn from this course:

• Learn the basic fundamentals of fraud detection model
• Learn how credit card fraud detection models work. This section will cover data collection, feature selection, model training, real time processing, and post alert action
• Learn about most common credit card fraud cases like stolen card, card skimming, phishing attack, identity theft, data breach, and insider fraud
• Learn how to find and download datasets from Kaggle
• Learn how to clean dataset by removing missing rows and duplicate values
• Learn how to evaluate the security of chip and pin transaction methods
• Learn how to analyze and identify repeat retailer fraud patterns
• Learn how to find correlation between transaction amount and fraud
• Learn how to analyze fraud cases in online transaction
• Learn how to conduct feature selection using Random Forest
• Learn how to build credit card fraud detection model using Random Forest
• Learn how to build credit card fraud detection model using Logistic Regression
• Learn how to build credit card fraud detection model using Support Vector Machine
• Learn how to evaluate fraud detection model’s accuracy and performance using precision, recall, and F1 score