Fraud Detection Using OpenShift Data Science - A Step-by-Step Guide

Fraud Detection Using OpenShift Data Science - A Step-by-Step Guide

Explore a comprehensive AI/ML use case for detecting fraudulent transactions in financial institutions using Red Hat OpenShift Data Science (RHODS). Learn about the solution's flow, integration with partner ecosystems like Starburst, and follow a detailed step-by-step guide to set up and implement the fraud detection workflow. Discover how to create a data science project, utilize the query editor, clean and scale data, and perform necessary configurations and testing. Gain valuable insights into leveraging RHODS for effective fraud detection in a 45-minute tutorial that covers everything from introduction to final testing.