Open-source technologies allow developers to build microservices framework to build myriad real-time applications. One such application is building the real-time model scoring. In this session,
we will showcase how to architect a microservice framework, in particular how to use it to build a low-latency, real-time model scoring system. At the core of the architecture lies Apache Spark’s Structured
Streaming capability to deliver low-latency predictions coupled with Docker and Flask as additional open source tools for model service. In this session, you will walk away with:
* Knowledge of enterprise-grade model as a service
* Streaming architecture design principles enabling real-time machine learning
* Key concepts and building blocks for real-time model scoring
* Real-time and production use cases across industries, such as IIOT, predictive maintenance, fraud detection, sepsis etc.
Session hashtag: #SAISStreaming1