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Edge AI is transforming the way computers interact with the real
world, allowing IoT devices to make decisions using the 99% of
sensor data that was previously discarded due to cost, bandwidth,
or power limitations. With techniques like embedded machine
learning, developers can capture human intuition and deploy it to
any target--from ultra-low power microcontrollers to embedded Linux
devices. This practical guide gives engineering professionals,
including product managers and technology leaders, an end-to-end
framework for solving real-world industrial, commercial, and
scientific problems with edge AI. You'll explore every stage of the
process, from data collection to model optimization to tuning and
testing, as you learn how to design and support edge AI and
embedded ML products. Edge AI is destined to become a standard tool
for systems engineers. This high-level road map helps you get
started. Develop your expertise in AI and ML for edge devices
Understand which projects are best solved with edge AI Explore key
design patterns for edge AI apps Learn an iterative workflow for
developing AI systems Build a team with the skills to solve
real-world problems Follow a responsible AI process to create
effective products
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