Overview
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Explore the potential of TinyML in developing countries through this insightful talk by Pete Warden, Technical Lead of TensorFlow Lite at Google. Discover how machine learning on small, affordable, battery-powered devices can revolutionize fields such as medicine, agriculture, consumer electronics, and wildlife conservation. Learn about the advantages of TinyML in areas with limited data coverage and its adaptability to local conditions and languages. Gain valuable insights into the underlying technology, its applications in Kenya, and the opportunities it presents for researchers and startups. Delve into topics such as embedded systems, multilingual spoken words, African radio, federated learning, and hardware considerations. Get practical advice on getting started with TinyML, including working with microcontrollers, Raspberry Pi, and MicroBit. Understand the challenges and potential solutions for memory constraints in embedded devices, and explore the educational and collaborative aspects of TinyML in the developing world.
Syllabus
Introduction
Who am I
What is tinyML
Plant Village
Wildlabsnet
Smartphones vs TinyML
Embedded Systems
Developing Countries
Education
Collaborations
TinyML 4D
Multilingual Spoken Words
African Radio
federated learning
easier problems
TinyML examples
Raspberry Pi
Microcontroller Performance
Hardware
Batteries
MicroBit
Getting started
Embedded devices
General advice
Memory constraints
Taught by
tinyML