內容簡介:結合人工智慧與超低功耗嵌入式裝置，讓這個世界更聰明本書介紹TinyML這項快速發展的技術，結合了機器學習與嵌入式系統，讓微控制器這類超低功耗裝置上得以實現AI。在開頭會先針對這個整合了諸多學科的領域進行了相當實用的介紹，讓您可快速理解要在Arduino Nano 33 BLE Sense與Raspberry Pi Pico上部署智能應用的關鍵點。本書可以幫助你了解如何處理在製作微處理器原型時所碰到的各種問題，例如透過GPIO腳位來控制LED狀態、讀取按鈕狀態，以及透過電池來對微處理器供電。並且會帶著你實作與溫度、濕度與三V感測器(語音、視覺與振動)有關的專題，並從中理解在不同情境中實作端對端智能應用的必要技術。接著，告訴你如何為記憶體有限的微處理器來建置微型模型的最佳方案。最後會介紹兩項最新的技術：microTVM 與microNPU，讓你在TinyML領域中更上一層樓。看完本書之後，可以幫助你建立各種最佳實作方案與機器學習框架的基本概念，知道如何輕鬆在各種微控制器上部署機器學習app，並且對於開發階段所要考量的關鍵因素有清楚的理解。本書精彩內容包括：．理解微控制器程式設計的重要基礎觀念．操作真實感測器，包含麥克風、照相機與加速度計．運用TensorFlow Lite for Microcontrollers框架在各種裝置上執行機器學習應用．使用Edge Impulse開發可回應人類語音的app．操作Arduino Nano 33 BLE Sense並搭配遷移學習技術來分類室內環境。．使用Raspberry Pi Pico來製作手勢辨識app．設計可用於記憶體受限之微控制器的CIFAR-10模型．在虛擬的Arm Ethos-U55 microNPU上搭配microTVM來執行影像分類器
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