TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers
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TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers

by Daniel Situnayake, Pete Warden

Programming Machine Learning Embedded Systems
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TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers offers an introduction to running machine learning on compact, energy-efficient hardware. Daniel Situnayake and Pete Warden explore the tools and concepts behind TinyML, helping readers understand this emerging area of embedded technology.

About This Book

TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers introduces machine learning for small, resource-constrained devices.

Written by Daniel Situnayake and Pete Warden, the book focuses on using TensorFlow Lite with Arduino and ultra-low-power microcontrollers.

It provides an accessible entry point for readers interested in combining embedded systems with machine learning.

The book is suited to learners, makers, and developers exploring how intelligent applications can run on compact hardware.

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I will be using this book for: