Udemy – Building Credit Card Fraud Detection with Machine Learning 2024-1

Building Credit Card Fraud Detection with Machine Learning course. This course teaches you step-by-step how to build a fraud detection model for credit card transactions using machine learning algorithms such as logistic regression, support vector machines, and random forests. In this course, you will first learn the basic concepts of fraud detection and its common challenges. Then, you will explore the complete steps of building a model, from data collection and feature extraction to model training and real-time processing. You will also learn about common types of fraud such as card theft, skimming, phishing, and data breaches. In the practical part, you will learn how to set up a Google Colab environment, download a dataset from Kaggle, and clean the data. Next, you will learn about data analysis methods, fraud pattern identification, and feature selection, and implement and evaluate different models. Finally, the accuracy of the model is measured using metrics such as Precision, Recall, and F1-Score. This course will not only strengthen your data science skills but also help you provide effective solutions for financial security, given the rise in fraud in online transactions.

What you will learn:

• How to build a credit card fraud detection model using Random Forest, Logistic Regression, and Support Vector Machine
• How to do Feature Selection using Random Forest
• How to analyze and identify repeat retailer fraud patterns
• How to analyze online transaction fraud
• How to assess the security of Chip and Pin transaction methods
• How to find correlation between transaction amount and fraud
• How credit card fraud detection models work. This section will cover Data Collection, Feature Selection, Model Training, and Real Time Processing.
• How to evaluate the accuracy and performance of a fraud detection model using Precision, Recall, and F1 Score
• Familiarity with the most common credit card fraud cases such as Stolen Card, Card Skimming, Phishing Attack, Identity Theft, Data Breach, and Insider Fraud
• Learning the basics of fraud detection models
• How to find and download datasets from Kaggle
• How to clean up a dataset by removing missing rows and duplicate values

Who is this course suitable for?

• People who are interested in building a credit card fraud detection model using Machine Learning.
• People who are interested in performing Feature Selection using Random Forest.

Course details: Building Credit Card Fraud Detection with Machine Learning

• Publisher:  Udemy
• Instructor:  Christ Raharja
• Training level: Beginner to advanced
• Training duration: 3 hours and 5 minutes
• Number of lessons: 22

Course topics

Prerequisites for the Building Credit Card Fraud Detection with Machine Learning course

• No previous experience in machine learning is required
• Basic knowledge in statistics and Python

Course images

Sample course video

Download link

Download file – 0.98 GB

File(s) password: www.downloadly.ir

File size

0.98 GB