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Author Warden, Pete, author.

Title TinyML : machine learning with TensorFlow Lite on Arduino and ultra-low power microcontrollers / Pete Warden and Daniel Situnayake

Edition First edition
Publication Info. Sebastopol, CA : O'Reilly Media Inc., [2020]
©2020
Location Call No. Status
 Nichols Adult Nonfiction-NEW  006.31 TEN 2020    DUE 08-24-20
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Description xvi, 484 pages : illustrations ; 24 cm
Note Includes index
Summary Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size-- small enough to run on a microcontroller. With this practical book you'll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices. Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary
Subject Machine learning.
Signal processing -- Digital techniques.
TinyML.
TensorFlow.
Microcontrollers.
Added Author Situnayake, Daniel, author.
ISBN 9781492052043
1492052043
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