TinyML : li yu TensorFlow Lite zai Arduino he chao di gong hao wei kong zhi qi shang bu shu ji qi xue xi = TinyML : machine learning with TensorFlow Lite on Arduino and ultra-low-power microcontrollers /

TinyML : li yu TensorFlow Lite zai Arduino he chao di gong hao wei kong zhi qi shang bu shu ji qi xue xi = TinyML : machine learning with TensorFlow Lite on Arduino and ultra-low-power microcontrollers /

TinyML : 基于TensorFlow Lite 在 Arduino 和超低功耗微控制器上部署机器学习 = TinyML : machine learning with TensorFlow Lite on Arduino and ultra-low-power microcontrollers /

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Bibliographic Details
Author / Creator:	Warden, Pete, author.
Uniform title:	TinyML. Chinese
Edition:	Di 1 ban. 第1版.
Imprint:	Beijing： Ji xie gong ye chu ban she, 2020. 北京 : 机械工业出版社, 2020.
Description:	1 online resource (434 pages) : illustrations.
Language:	Chinese
Series:	O'Reilly jing pin tu shu xi lie O'Reilly精品图书系列 O'Reilly jing pin tu shu xi lie. O'Reilly精品图书系列.
Subject:	TensorFlow. Machine learning. Signal processing -- Digital techniques. Microcontrollers. Machine learning Microcontrollers Signal processing -- Digital techniques
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/13696777

Hidden Bibliographic Details
Varying Form of Title:	TinyML : machine learning with TensorFlow Lite on Arduino and ultra-low-power microcontrollers
Other authors / contributors:	Situnayake, Daniel, author. Wei, Lan, translator. Bu, Jie, translator. 魏兰, translator. 卜杰, translator.
Notes:	"Hua zhang IT." "华章IT."
Summary:	Detailed summary in vernacular field. 深度学习网络正在变得越来越小。Google Assistant团队可以使用大小只有14KB的模型检测单词----模型小到可以在微控制器上运行。在这本实用的书中，你将进入TinyML的世界。TinyML将深度学习和嵌入式系统相结合，使得微型设备可以做出令人惊叹的事情。本书解释了如何训练足够小的模型以适合任何环境。对于希望在嵌入式系统中搭建机器学习项目的软件及硬件开发人员而言，本书是一个理想的指南，它将一步步地指导你搭建一系列TinyML项目。阅读本书不需要任何机器学习或者微控制器开发经验。你将深入了解以下内容：如何创建语音识别程序、行人检测程序和响应手势的魔杖程序。如何使用Arduino和超低功耗微控制器。机器学习的基本知识以及如何训练自己的模型。如何训练模型以理解音频、图像和加速度传感器数据。如何使用TensorFlow Lite for Microcontrollers，这是Google用于TinyML的工具包。如何调试程序并提供隐私和安全保障。如何优化延迟、功耗、模型以及二进制文件大小。.
Standard no.:	9787111664222