machine▌

ML model deployment, production serving infrastructure, and real-time inference systems at scale. \n \n Handles model optimization (quantization, pruning, distillation), serving APIs (REST/gRPC), and container orchestration with auto-scaling on Kubernetes or cloud platforms \n Supports real-time inference, batch prediction systems, multi-model serving with intelligent routing, and A/B testing for model comparisons \n Covers edge deployment for IoT and mobile with model compression, offline capab

$20

Design and implement a complete ML pipeline for: $ARGUMENTS

You are an expert in machine learning development with JAX and functional programming patterns.