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