TinyML : (Record no. 14965)

MARC details
000 -LEADER
fixed length control field 02165cam a22002777a 4500
001 - CONTROL NUMBER
control field TB12444
003 - CONTROL NUMBER IDENTIFIER
control field IN-BhIIT
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260310154943.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 210714s2020 cc a 001 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9789352139606 (PBK)
040 ## - CATALOGING SOURCE
Original cataloging agency IN-BhIIT
041 ## - LANGUAGE CODE
Language code of text eng
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Book number WAR/T
100 1# - MAIN ENTRY--AUTHOR NAME
Personal name Warden, Pete
Relator term Author
245 10 - TITLE STATEMENT
Title TinyML :
Sub Title machine learning with tensorflow lite on arduino and ultra-low-power microcontrollers /
Statement of responsibility, etc Pete Warden and Daniel Situnayake.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication Mumbai :
Name of publisher O'Relly Media Inc.,
Year of publication 2021.
300 ## - PHYSICAL DESCRIPTION
Number of Pages xvi, 484 pages :
Other physical details(ill.) illustrations ;
Dimensions(size) 24 cm
500 ## - GENERAL NOTE
General note Includes bibliographical references and index.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Introduction -- Getting started -- Getting up to speed on machine learning -- The "Hello world" of TinyML : building and training a model -- The "Hello world" of TinyML : building an application -- The "Hello world" of TinyML : deploying to microcontrollers -- Wake-word detection : building an application -- Wake-word detection : training a model -- Person detection : building an application -- Person detection : training a model -- Magic wand : building an application -- Magic wand : training a model -- TensorFlow lite for microcontrollers -- Designing your own TinyML applications -- Optimizing latency -- Optimizing energy usage -- Optimizing model and binary size -- Debugging -- Porting models from TensorFlow to TensorFlow Lite -- Privacy, security, and deployment -- Learning more.
520 ## - SUMMARY, ETC.
Summary, etc Deep learning networks are becoming smaller, with models as small as 14 kilobytes. This practical book, TinyML, combines deep learning and embedded systems to create small, portable devices. It provides a step-by-step guide for developers to create TinyML projects, including speech recognition, camera detection, and gesture response. The book also covers learning ML basics, using TensorFlow Lite for microcontrollers, and optimizing latency and energy usage.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Machine learning.
Topical Term Signal processing
General subdivision Digital techniques.
Topical Term Microcontrollers.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Situnayake, Daniel
Relator term Joint author
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Text Book
Koha issues (borrowed), all copies 2
Holdings
Withdrawn status Lost status Damaged status Not for loan Collection code Home library Current library Date acquired Source of acquisition Cost, normal purchase price Full call number Accession Number Cost, replacement price Price effective from Koha item type
Not withdrawn Not Lost not damaged   SMS Central Library, IIT Bhubaneswar Central Library, IIT Bhubaneswar 06/03/2025 22 1425.00 006.31 WAR/T TB12444 1900.00 06/03/2025 Text Book

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