Model Serving

Model serving involves setting up infrastructure to handle prediction requests at scale. This includes request routing, load balancing, model loading, inference optimization, and response handling. The technical infrastructure includes performance optimization, scaling mechanisms, and caching systems, with considerations for latency, throughput, and resource utilization.

Real-time prediction services Batch inference systems API endpoints High-performance model deployment