Connecting requirements to the machine-learning assurance lifecycle

Overview

Outlines an iterative ML lifecycle comprising data management, model learning, verification and deployment. It explains how system requirements and operating constraints inform ML requirements and how stage activities and artefacts contribute to assurance of the deployed component.