Description: Title: Tinyml: Machine Learning with Tensorflow Lite on Arduino and Ultra-Low-Power Microcontrollers Author: Warden, Pete Publisher: O'Reilly Media Binding: Paperback Pages: 501 Dimensions: 9.17h x 7.01w x 1.01d Product Weight: 1.75 lbs. Language: English ISBN: 9781492052043 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. As of early 2022, the supplemental code files are available at https: //oreil.ly/XuIQ4. 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. Build a speech recognizer, a camera that detects people, and a magic wand that responds to gestures Work with Arduino and ultra-low-power microcontrollers Learn the essentials of ML and how to train your own models Train models to understand audio, image, and accelerometer data Explore TensorFlow Lite for Microcontrollers, Google's toolkit for TinyML Debug applications and provide safeguards for privacy and security Optimize latency, energy usage, and model and binary size Ships Fast From The USA! Authorized Dealer
Price: 54.99 USD
Location: Milwaukee, Wisconsin
End Time: 2024-11-04T21:44:51.000Z
Shipping Cost: 9.95 USD
Product Images
Item Specifics
Restocking Fee: No
Return shipping will be paid by: Seller
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
Book Title: does not apply
MPN: does not apply
Number of Pages: 501 Pages
Language: English
Publication Name: Tinyml : Machine Learning with Tensorflow Lite on Arduino and Ultra-Low-Power Microcontrollers
Publisher: O'reilly Media, Incorporated
Subject: Data Modeling & Design, General, Computer Vision & Pattern Recognition
Item Height: 1.1 in
Publication Year: 2020
Type: Textbook
Item Weight: 30 Oz
Subject Area: Computers, Science
Item Length: 9.1 in
Author: Daniel Situnayake, Pete Warden
Item Width: 7 in
Format: Trade Paperback
