MARC details
| 000 -LEADER |
|---|
| fixed length control field |
02792nam a22003977a 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
22132416 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
IIITD |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20230907124830.0 |
| 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 |
9789352139606 |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(OCoLC)on1104044619 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
YDX |
| Language of cataloging |
eng |
| Transcribing agency |
YDX |
| 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 |
| Edition number |
23 |
| Item number |
WAR-T |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Warden, Pete |
| 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 |
by Pete Warden and Daniel Situnayake |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc |
New Delhi : |
| Name of publisher, distributor, etc |
Shroff Publishers, |
| Date of publication, distribution, etc |
©2021 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xvi, 484 p. : |
| Other physical details |
ill. ; |
| Dimensions |
24 cm |
| 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 as entry element |
Machine learning. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Signal processing |
| General subdivision |
Digital techniques. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Microcontrollers. |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Machine learning. |
| Source of heading or term |
fast |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Microcontrollers. |
| Source of heading or term |
fast |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Signal processing |
| General subdivision |
Digital techniques. |
| Source of heading or term |
fast |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Situnayake, Daniel |
| 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 |
Books |
