April 2022
Intermediate to advanced
344 pages
7h 18m
English
Overview
In the "TinyML Cookbook," you'll delve into the rapidly evolving field of TinyML, a groundbreaking combination of machine learning and low-power embedded systems. The book provides clear and concise recipes to help you develop, train, and deploy machine learning models on microcontroller devices like Arduino Nano 33 BLE Sense and Raspberry Pi Pico.
What this Book will help me do
- Train and deploy TinyML models on ARM-based microcontroller devices.
- Understand and utilize sensors to gather data for machine learning applications.
- Build intelligent IoT applications with real-time data processing capabilities.
- Implement microcontroller-based solutions using TensorFlow Lite for Microcontrollers.
- Leverage transfer learning to enhance TinyML model performance.
Author(s)
Gian Marco Iodice is a seasoned engineer and researcher specializing in machine learning for embedded systems. With years of experience in software development and AI, he brings a practical perspective to TinyML. Gian's passion lies in teaching others by breaking down complex concepts into approachable, hands-on guides.
Who is it for?
This book is perfect for software developers and machine learning enthusiasts keen on embedding intelligent behavior into small devices. While some familiarity with Python or C/C++ is expected, no prior experience with microcontrollers is required. By following this guide, you'll achieve a practical understanding of deploying ML on constrained hardware. If you're eager to innovate with low-power AI applications, this book is your starting point.
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