TinyML in Practice: Deploying Intelligent Machine Learning on Microcontrollers for Real-World Applications - Tapa blanda

Sinopsis

Build smarter systems on the smallest devices.

TinyML in Practice is your hands-on guide to deploying machine learning models on microcontrollers and ultra-low-power hardware. Whether you're building voice-activated sensors, predictive maintenance tools, or intelligent wearables, this book walks you through every step — from data collection and model training to optimization, deployment, and long-term lifecycle management.

Inside, you'll learn: • How to choose the right microcontroller for your ML task • Techniques for collecting and preprocessing sensor data • Model optimization strategies including quantization and pruning • Power management and communication design for battery-powered systems • Security, privacy, and OTA update frameworks for real-world deployments

With full-length chapters, real-world blueprints, and future-facing insights, this book is perfect for embedded engineers, ML developers, and makers who want to bring intelligence to the edge.

No cloud required. No hype. Just real TinyML, done right.

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