Tinyml: Machine Learning with Tensorflow Lite on Arduino and Ultra-Low-Power Microcontrollers Contributor(s): Warden, Pete (Author), Situnayake, Daniel (Author) |
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ISBN: 1492052043 ISBN-13: 9781492052043 Publisher: O'Reilly Media OUR PRICE: $44.99 Product Type: Paperback - Other Formats Published: January 2020 |
Additional Information |
BISAC Categories: - Computers | Embedded Computer Systems - Computers | Image Processing - Computers | Computer Vision & Pattern Recognition |
Physical Information: 1.01" H x 7.01" W x 9.17" (1.75 lbs) 504 pages |
Descriptions, Reviews, Etc. |
Publisher Description: 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.
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Contributor Bio(s): Situnayake, Daniel: - 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. Warden, Pete: -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. |