Doubling the Performance of AI for Fraud Detection with Graph
Build a payment fraud detection system with TigerGraph and Python ML. Reduce fraud by 50% and minimize false positives. Learn how!
Course Content
Doubling the Performance of AI for Fraud Detection with Graph is an intermediate-level Pluralsight course taught by Big Data LDN. It runs 43m, is taught in English, and includes a certificate of completion. It is a paid course, first published September 2023.
Build a Powerful Payment Fraud Detection System
Discover how to significantly reduce payment fraud and minimize false positives with a practical demonstration of TigerGraph and Python machine learning. This session provides a comprehensive look at creating an effective fraud detection system that can halve fraud occurrences while reducing inappropriate transaction blocks.
Richard will walk you through the entire process, covering:
- Data Preparation: Learn how to structure and prepare your payment data for optimal analysis.
- System Architecture: Understand the architecture of a robust payment fraud detection system leveraging TigerGraph.
- Python Machine Learning Integration: Explore how to integrate Python machine learning techniques for enhanced fraud detection capabilities.
- Code Walkthrough: Get hands-on with the code used to build and deploy the system.
This demonstration is perfect for anyone looking to improve their payment security and streamline transaction processing. Learn to leverage the power of graph databases and machine learning to create a more resilient and efficient payment system.
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