Building a scalable ML model serving API with Ray Serve

The demo will show how to:
- Deploy a trained Python model and scale it to a cluster using Ray Serve
- Improve the HTTP API using Ray Serve’s native FastAPI integration
- Compose multiple independently-scalable models into a single model, and run them in parallel to minimize latency.

LinkView slides >>>