Fraud detection with Machine Learning

This document discusses using machine learning for fraud detection. It outlines how machine learning can provide a scalable, adaptable solution to identify fraud. The machine learning pipeline involves gathering data from user accounts, selecting a model like CatBoost that handles categorical data well, training and evaluating the model, and deploying the trained model to classify new users as fraudulent or not. The goal is to balance avoiding false positives and false negatives when identifying fraud.Read less