MARC details
| 000 -LEADER |
|---|
| fixed length control field |
02756nam a22004337i 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
1306240662 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
OCoLC |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20241025141747.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS |
|---|
| fixed length control field |
m o d |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
|---|
| fixed length control field |
cr cnu|||unuuu |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
220329s2022 enka o 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| Canceled/invalid ISBN |
9781803247335 |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(OCoLC)1306240662 |
| 037 ## - SOURCE OF ACQUISITION |
|---|
| Stock number |
9781803247335 |
| Source of stock number/acquisition |
O'Reilly Media |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
ORMDA |
| Language of cataloging |
eng |
| Description conventions |
rda |
| -- |
pn |
| Transcribing agency |
ORMDA |
| Modifying agency |
OCLCO |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
Q336 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
006.3 ROT 2022 |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Rothman, Denis, |
| Relator term |
author |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Transformers for natural language processing : |
| Remainder of title |
build, train, and fine-tuning deep neural network architectures for NLP with Python, Hugging face, and openAI's GPT-3, ChatGPT, and GPT4 / |
| Statement of responsibility, etc. |
Denis Rothman ; foreword by Antonio Gulli |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
Second edition |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
[Birmingham, United Kingdom] : |
| Name of producer, publisher, distributor, manufacturer |
Packt Publishing, |
| Date of production, publication, distribution, manufacture, or copyright notice |
[2022] |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxiii, 565 pages : |
| Other physical details |
illustrations ; |
| Dimensions |
23 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 |
| 490 1# - SERIES STATEMENT |
|---|
| Series statement |
Expert insight |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Includes index |
| 506 ## - RESTRICTIONS ON ACCESS NOTE |
|---|
| Terms governing access |
Available to OhioLINK libraries |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Transformers are a game-changer for natural language understanding (NLU) and have become one of the pillars of artificial intelligence. Transformers for Natural Language Processing, 2nd Edition, investigates deep learning for machine translations, speech-to-text, text-to-speech, language modeling, question-answering, and many more NLP domains with transformers. An Industry 4.0 AI specialist needs to be adaptable; knowing just one NLP platform is not enough anymore. Different platforms have different benefits depending on the application, whether it's cost, flexibility, ease of implementation, results, or performance. In this book, we analyze numerous use cases with Hugging Face, Google Trax, OpenAI, and AllenNLP. This book takes transformers' capabilities further by combining multiple NLP techniques, such as sentiment analysis, named entity recognition, and semantic role labeling, to analyze complex use cases, such as dissecting fake news on Twitter. Also, see how transformers can create code using just a brief description. By the end of this NLP book, you will understand transformers from a cognitive science perspective and be proficient in applying pretrained transformer models to various datasets |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Artificial intelligence |
| General subdivision |
Data processing |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Artificial intelligence |
| General subdivision |
Computer programs |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Python (Computer program language) |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Cloud computing |
| 655 #4 - INDEX TERM--GENRE/FORM |
|---|
| Genre/form data or focus term |
Electronic books |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Gulli, Antonio, |
| Relator term |
writer of forewrod |
| 710 2# - ADDED ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
Ohio Library and Information Network |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Expert insight |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Open Collection |
