Model Optimization & Deployment

Model Optimization & Deployment

Taking a trained model from research checkpoint to production — quantization, pruning, distillation, and graph-level optimization, then packaging, serving, and the monitoring that keeps it working once it’s live. Treats the pipeline as a continuous loop, not a one-time handoff.

→ Slide Deck: Model Optimization & Deployment