MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03043cam a22004457a 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
22132416 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
VITAP |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20250322125327.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
210714s2020 cc a 001 0 eng d |
| 010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
|---|
| LC control number |
2020277178 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781492052043 |
| Qualifying information |
(paperback) |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(OCoLC)on1104044619 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
YDX |
| Language of cataloging |
eng |
| Transcribing agency |
VITAP |
| Modifying agency |
BDX |
| -- |
JRZ |
| -- |
CLE |
| -- |
OCLCF |
| -- |
DLC |
| 042 ## - AUTHENTICATION CODE |
|---|
| Authentication code |
lccopycat |
| 050 00 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
Q325.5 |
| Item number |
.W37 2020 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
006.31 WAR |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Warden, Pete, |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
TinyML : |
| Remainder of title |
machine learning with TensorFlow Lite on Arduino and ultra-low-power microcontrollers / |
| Statement of responsibility, etc. |
Pete Warden and Daniel Situnayake. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
First edition. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Beijing |
| -- |
Boston : |
| Name of producer, publisher, distributor, manufacturer |
O'Reilly, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2020. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xvi, 484p.: ill.: 23cm |
| Other physical details |
illustrations ; |
| Dimensions |
24 cm |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
unmediated |
| Media type code |
n |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
volume |
| Carrier type code |
nc |
| Source |
rdacarrier |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Includes 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 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. |
| 630 00 - SUBJECT ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
TensorFlow. |
| 630 04 - SUBJECT ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
TinyML. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Machine learning. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Signal processing |
| General subdivision |
Digital techniques. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Microcontrollers. |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Machine learning. |
| Source of heading or term |
fast |
| Authority record control number or standard number |
(OCoLC)fst01004795 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Microcontrollers. |
| Source of heading or term |
fast |
| Authority record control number or standard number |
(OCoLC)fst01744800 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Signal processing |
| General subdivision |
Digital techniques. |
| Source of heading or term |
fast |
| Authority record control number or standard number |
(OCoLC)fst01118285 |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Situnayake, Daniel, |
| Relator term |
author |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) |
|---|
| a |
7 |
| b |
cbc |
| c |
copycat |
| d |
2 |
| e |
ncip |
| f |
20 |
| g |
y-gencatlg |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Text Book |
