Building Credit Card Fraud Detection with Machine Learning
Learn how to build credit card fraud detection model using Random Forest, Logistic Regression and Support Vector Machine
4.37 (52 reviews)
3 170
students
3 hours
content
Jan 2024
last update
$13.99
regular price
What you will learn
Learn how to build credit card fraud detection model using Random Forest, Logistic Regression, and Support Vector Machine
Learn how to conduct feature selection using Random Forest
Learn how to analyze and identify repeat retailer fraud patterns
Learn how to analyze fraud cases in online transaction
Learn how to evaluate the security of chip and pin transaction methods
Learn how to find correlation between transaction amount and fraud
Learn how credit card fraud detection models work. This section will cover data collection, feature selection, model training, and real time processing
Learn how to evaluate fraud detection model’s accuracy and performance using precision, recall, and F1 score
Learn about most common credit card fraud cases like stolen card, card skimming, phishing attack, identity theft, data breach, and insider fraud
Learn the basic fundamentals of fraud detection model
Learn how to find and download datasets from Kaggle
Learn how to clean dataset by removing missing rows and duplicate values
Course Gallery
Loading charts...
5778452
udemy ID
22/01/2024
course created date
29/01/2024
course indexed date
Bot
course submited by