MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03655cam a22005175i 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
21736935 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20220412104404.0 |
| 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 ||||||||||| |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
171206s2017 xxu|||| o |||| 0|eng |
| 010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
|---|
| LC control number |
2019754609 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781484230961 |
| 024 7# - OTHER STANDARD IDENTIFIER |
|---|
| Standard number or code |
10.1007/978-1-4842-3096-1 |
| Source of number or code |
doi |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(DE-He213)978-1-4842-3096-1 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
DLC |
| Language of cataloging |
eng |
| Description conventions |
pn |
| -- |
rda |
| Transcribing agency |
DLC |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
COM004000 |
| Source |
bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
UYQ |
| Source |
bicssc |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
UYQ |
| Source |
thema |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
005.76813 |
| Edition number |
1 |
| Item number |
PATS |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Pattanayak, Santanu. |
| 9 (RLIN) |
29464 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Pro Deep Learning with TensorFlow : |
| Remainder of title |
a mathematical approach to advanced artificial intelligence in python / |
| Statement of responsibility, etc. |
By Santanu Pattanayak. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
1st ed. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
New York : |
| Name of publisher, distributor, etc. |
Apress , |
| Date of publication, distribution, etc. |
2020 |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Berkeley, CA : |
| Name of producer, publisher, distributor, manufacturer |
Apress : |
| -- |
Imprint: Apress, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2017. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxi, 397p. |
| Dimensions |
24 cm. |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
computer |
| Media type code |
c |
| Source |
rdamedia |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Chapter 1: Mathematical Foundations -- Chapter 2: Introduction to Deep Learning Concepts and TensorFlow -- Chapter 3: Convolutional Neural Networks -- Chapter 4: Natural Language Processing Using Recursive Neural Networks -- Chapter 5: Unsupervised Learning with Restricted Boltzmann Machines and Auto Encoders -- Chapter 6: Advanced Neural Networks. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Deploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition required to invent new deep learning architectures and solutions on your own. Pro Deep Learning with TensorFlow provides practical, hands-on expertise so you can learn deep learning from scratch and deploy meaningful deep learning solutions. This book will allow you to get up to speed quickly using TensorFlow and to optimize different deep learning architectures. All of the practical aspects of deep learning that are relevant in any industry are emphasized in this book. You will be able to use the prototypes demonstrated to build new deep learning applications. The code presented in the book is available in the form of iPython notebooks and scripts which allow you to try out examples and extend them in interesting ways. You will be equipped with the mathematical foundation and scientific knowledge to pursue research in this field and give back to the community. What You'll Learn: Understand full stack deep learning using TensorFlow and gain a solid mathematical foundation for deep learning Deploy complex deep learning solutions in production using TensorFlow Carry out research on deep learning and perform experiments using TensorFlow. |
| 588 ## - SOURCE OF DESCRIPTION NOTE |
|---|
| Source of description note |
Description based on publisher-supplied MARC data. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Mathematical foundations |
| 9 (RLIN) |
29465 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Convolutional neural networks |
| 9 (RLIN) |
29466 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Advanced neural networks |
| 9 (RLIN) |
29467 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Big data. |
| 9 (RLIN) |
29468 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Python (Computer program language). |
| 9 (RLIN) |
29469 |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Artificial Intelligence. |
| Authority record control number or standard number |
https://scigraph.springernature.com/ontologies/product-market-codes/I21000 |
| 9 (RLIN) |
29470 |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Big Data. |
| Authority record control number or standard number |
https://scigraph.springernature.com/ontologies/product-market-codes/I29120 |
| 9 (RLIN) |
29471 |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Python. |
| Authority record control number or standard number |
https://scigraph.springernature.com/ontologies/product-market-codes/I29080 |
| 9 (RLIN) |
29472 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Print version: |
| Title |
Pro deep learning with tensorflow |
| International Standard Book Number |
9781484230954 |
| Record control number |
(DLC) 2017962327 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Printed edition: |
| International Standard Book Number |
9781484230954 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Printed edition: |
| International Standard Book Number |
9781484230978 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Printed edition: |
| International Standard Book Number |
9781484252499 |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) |
|---|
| a |
0 |
| b |
ibc |
| c |
origres |
| d |
u |
| e |
ncip |
| f |
20 |
| g |
y-gencatlg |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Book |
| Edition |
1st |
| Call number prefix |
005.76813 PATS |
