Edge AI on Embedded Devices Running Machine Learning on Microcontrollers and Low-Power Hardware
Language: English
Published by Independently Published, 2025
- Softcover
- New

Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
AbeBooks seller since June 11, 1999
Condition: New
US$ 39.06
Quantity: Over 20 available
Add to basketItem description from seller
Seller Inventory # L2-9798241712158
- Title
- Edge AI on Embedded Devices Running Machine Learning on Microcontrollers and Low-Power Hardware
- Author
- Byte Weaver
- Publisher
- Independently Published
- Publication year
- 2025
- Condition
- New
- Binding
- PAP
- Language
- English
- ISBN 13
- 9798241712158
- Item weight
- 744 grams
Why this matters now: Billions of microcontrollers power our world—pacemakers, industrial sensors, smart infrastructure. Cloud AI can't reach them. This book shows how to build machine learning systems that thrive under constraints where standard ML practices break down.
What makes this different:
- Concrete trade-offs between accuracy, latency, memory, and power consumption on real hardware
- Model optimization techniques that preserve performance when kilobytes matter
- Deployment pipelines designed for resource-limited targets, not GPU clusters
- Security and maintenance strategies for devices in the field for decades
- Hardware selection frameworks that match model complexity to silicon capabilities
For practitioners: Written for engineers building production systems, not running benchmarks. Embedded developers learn ML constraints. ML engineers learn embedded realities. Both learn to design AI that survives deployment.
Build AI that runs where cloud computing ends. Start designing systems engineered for silicon, not slides.
"Synopsis" may belong to another edition of this title.
PBShop.store UK
Fairford, GLOS, United Kingdom
AbeBooks seller since June 11, 1999
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