A Better Way to Build a Fraud Detector: Streaming Data and Microservices Architecture | Whiteboard Walkthrough

In this Whiteboard Walkthrough Ted Dunning, Chief Application Architect at MapR, provides some pointers for building better machine learning models, including the advantages of data streams and microservices style design in the example of a credit card fraud detector, the need for metrics, and how reconstruction of data from an auto-encoder can serve as a figure of merit that helps identify good models.

For additional resources on fraud detection, anomaly detection, microservices and streaming data: