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Explore practical applications of embedded machine learning on microcontroller units (MCUs) in this 57-minute technical talk delivered by NXP's Machine Learning Architecture Engineer Jongmin Lee. Learn how deploying ML models on edge devices reduces data traffic between edge and cloud, minimizes latency, and enhances privacy by eliminating raw data transmission to the cloud. Discover key examples of MCU-based ML applications and their real-world implementations, while gaining insights into the substantial performance improvements possible through Neural Processing Unit enabled MCUs. Understand how recent developments in MCU hardware technology and ML model compression techniques have made it possible to deploy efficient lightweight ML models with impressive performance on edge devices.
