Tinyml: Machine Learning with Tensorflow Lite on Arduino and Ultra-Low-Power Microcontrollers (Paperback)

Warden, Pete, Situnayake, Daniel




Neural networks are getting smaller. Much smaller. The OK Google team, for example, has run machine learning models that are just 14 kilobytes in size--small enough to work on the digital signal processor in an Android phone. With this practical book, you'll learn about TensorFlow Lite for Microcontrollers, a miniscule machine learning library that allows you to run machine learning algorithms on tiny hardware.

Authors Pete Warden and Daniel Situnayake explain how you can train models that are small enough to fit into any environment, including small embedded devices that can run for a year or more on a single coin cell battery. Ideal for software and hardware developers who want to build embedded devices using machine learning, this guide shows you how to create a TinyML project step-by-step. No machine learning or microcontroller experience is necessary.

  • Learn practical machine learning applications on embedded devices, including simple uses such as speech recognition and gesture detection
  • Train models such as speech, accelerometer, and image recognition, you can deploy on Arduino and other embedded platforms
  • Understand how to work with Arduino and ultralow-power microcontrollers
  • Use techniques for optimizing latency, energy usage, and model and binary size


神經網絡變得越來越小。小得多。例如,OK Google團隊運行的機器學習模型只有14千字節的大小,足夠小以在Android手機的數字信號處理器上運行。通過這本實用書,您將了解TensorFlow Lite for Microcontrollers,這是一個微小的機器學習庫,可以在微小硬件上運行機器學習算法。

作者Pete Warden和Daniel Situnayake解釋了如何訓練足夠小以適應任何環境的模型,包括可以在單個硬幣電池上運行一年或更長時間的小型嵌入式設備。這本指南適用於希望使用機器學習構建嵌入式設備的軟件和硬件開發人員,並逐步展示了如何創建TinyML項目。不需要機器學習或微控制器經驗。

  • 學習在嵌入式設備上的實用機器學習應用,包括簡單的語音識別和手勢檢測等用途

  • 訓練可以部署在Arduino和其他嵌入式平台上的模型,如語音、加速度計和圖像識別

  • 了解如何使用Arduino和超低功耗微控制器

  • 使用優化延遲、能源使用和模型和二進制大小的技術


Pete Warden is technical lead for mobile and embedded TensorFlow. He was CTO and founder of Jetpac, which was acquired by Google in 2014, and previously worked at Apple. He was a founding member of the TensorFlow team, and blogs about practical deep learning at https: //petewarden.com.

Daniel Situnayake leads developer advocacy for TensorFlow Lite at Google. He co-founded Tiny Farms, the first US company using automation to produce insect protein at industrial scale. He began his career lecturing in automatic identification and data capture at Birmingham City University.


Pete Warden 是移動和嵌入式 TensorFlow 的技術主管。他曾是 Jetpac 的首席技術官和創始人,該公司於2014年被 Google 收購,之前曾在蘋果公司工作。他是 TensorFlow 團隊的創始成員之一,並在 https://petewarden.com 上寫博客,介紹實用的深度學習內容。

Daniel Situnayake 在 Google 負責 TensorFlow Lite 的開發者倡導工作。他是 Tiny Farms 的共同創辦人,該公司是美國第一家利用自動化技術大規模生產昆蟲蛋白的公司。他的職業生涯始於伯明翰城市大學的自動識別和數據捕獲講師。