Building effective real-time machine learning systems involves more than just deploying models; it requires robust streaming infrastructure and continuous feature aggregation. Teams must ensure high availability and responsiveness, especially for applications like fraud detection and personalized recommendations. The evolution of feature platforms is crucial, as they integrate with existing systems to streamline the productionization of machine learning workflows.
