{"id":9627,"date":"2026-08-10T10:09:36","date_gmt":"2026-08-10T10:09:36","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-building-credit-card-fraud-detection-with-machine-learning-2024-1\/"},"modified":"2026-08-10T10:09:36","modified_gmt":"2026-08-10T10:09:36","slug":"udemy-building-credit-card-fraud-detection-with-machine-learning-2024-1","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-building-credit-card-fraud-detection-with-machine-learning-2024-1\/","title":{"rendered":"Udemy \u2013 Building Credit Card Fraud Detection with Machine Learning 2024-1"},"content":{"rendered":"
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Description<\/span><\/h2>\n

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.<\/span><\/p>\n

What you will learn:<\/span><\/h3>\n