Next level Machine Learning with TinyML and Python
summary
Covers TinyML deployment of machine learning on microcontrollers, comparing hardware options and frameworks for interacting with sensors and running models. Discusses MicroPython and CircuitPython for microcontroller development and presents a real predictive-maintenance use case (anomaly prediction) plus example application areas like agriculture, conservation, health detection, ecology monitoring, and autonomous vehicles.
AI-written summary · about
related talks
25mMachine Learning on Microcontrollers; Tiny, Useful and Fun
01h 53mTinyML: Machine Learning’s Future is Tiny and Bright
29mMicrocontrollers + Machine Learning with MicroPython in 1-2-3
25mTinyML as-a-Service
31mKeynote: The next big thing in machine learning is tiny
36mTinyML at the Edge: Deploying and Optimizing AI Workloads on Zephyr RTOS
27mWhat’s TinyML good for
27mMicrocontrollers and Machine Learning with MicroPython and emlearn