Datasheets for Machine Learning Sensors - Standardization and Implementation
EDGE AI FOUNDATION via YouTube
Overview
Watch a technical talk exploring the development and implementation of standardized datasheets for machine learning sensors, presented by Harvard University postdoctoral researcher Matthew Stewart. Learn about the revolutionary impact of ML sensors in edge computing and data control, while discovering a comprehensive template for documenting sensor specifications. Explore essential components including hardware details, ML model characteristics, dataset attributes, end-to-end performance metrics, and environmental considerations. Understand how these datasheets enhance transparency, explainability, and user-friendliness in ML-enabled embedded systems, while promoting improved privacy and security measures. Gain insights into the importance of standardization across the ML community for responsible sensor data utilization, demonstrated through an exemplar datasheet presentation of an ML sensor implementation.
Syllabus
tinyML Talks: Datasheets for Machine Learning Sensors
Taught by
EDGE AI FOUNDATION