About This Training
Machine learning (ML) technology is fast becoming the heart of differentiated IoT devices, often defining the smart capabilities delivered. ML model monitoring, maintenance and updatability are essential to ensure that these smart capabilities continue to deliver the value promised throughout the lifecycle of the device, and require an MLOps strategy tailored to IoT scale.
In this session, NXP and AWS explore how to build and deploy ML solutions to many edge devices at scale and securely support MLOps for maintaining models through their lifecycle. You will learn how to address common MLOps challenges in the context of an IoT application running across multiple embedded devices.