There is no point of training Machine Learning models if there is no plan to make them available for applications to use. In this webinar, we are going to learn how to deploy an ML model as a REST API and leverage FIWARE components to enable real-time AI inference.

The use case covered involves getting data from different sources/organizations for real-time inference with a trained ML model.

Don’t miss this chance to learn the end-to-end implementation of the real-time inference AI service: ML Training, Docker setup, creating a Python Package, and implementing the ML API.