Learning deep learning : (Record no. 57681)

MARC details
000 -LEADER
fixed length control field 01821nam\a2200253\a\4500
001 - CONTROL NUMBER
control field 57681
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260118115516.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 260118s2021 mau 000 0 eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9789356063976
Qualifying information (paperback)
040 ## - CATALOGING SOURCE
Original cataloging agency DLC
Language of cataloging eng
Description conventions rda
Transcribing agency DLC
Modifying agency BD-DhIUB
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Edition number 22
Classification number 006.31
Item number E368l
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Ekman, Magnus,
Relator term author.
245 10 - TITLE STATEMENT
Title Learning deep learning :
Remainder of title theory and practice of neural networks, computer vision, nlp, and transformers using tensorflow /
Statement of responsibility, etc Magnus Ekman.
250 ## - EDITION STATEMENT
Edition statement First edition.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc India:
Name of publisher, distributor, etc Pearson India Education services Pvt. Ltd.,
Date of publication, distribution, etc 2022
300 ## - PHYSICAL DESCRIPTION
Extent pages cm
520 ## - SUMMARY, ETC.
Summary, etc "Deep learning is at the heart of many of today's most exciting advances in machine learning and artificial intelligence. Pioneering applications at companies like Tesla, Google, and Facebook are now being followed by massive investments in fields ranging from finance to healthcare. Now, there's a complete guide to deep learning with TensorFlow, the #1 Python library for building these breakthrough applications. Magnus Ekman illuminates both the underlying concepts and the hands-on programming techniques you'll need, even if you have no machine learning experience. Throughout, you'll find concise, well-annotated code examples using TensorFlow and the Keras API; for comparison and easy migration between frameworks, complementary examples in PyTorch are provided online. Ekman also explains enough of the mathematics to help newcomers grasp how deep learning actually works. The guide concludes by previewing emerging trends in deep learning, and exploring the challenging ethical issues surrounding its use"--
526 ## - STUDY PROGRAM INFORMATION NOTE
School name School of engineering, Technology &Sciences
Department Physical Science
Shelving Location Reference Stacks
541 ## - IMMEDIATE SOURCE OF ACQUISITION NOTE
Source of acquisition Risaam
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Deep learning
9 (RLIN) 7100
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Neural networks
9 (RLIN) 7078
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Serial Enumeration / chronology Total Checkouts Full call number Barcode Date last seen Copy number Cost, replacement price Price effective from Koha item type
Withdrawn after missing   Dewey Decimal Classification   Not For Loan Library, Independent University, Bangladesh (IUB) Library, Independent University, Bangladesh (IUB) Reference Stacks 24/12/2025 Purchase 1575.00 2022   006.31 E368l 029520 18/01/2026 01 3150.00 24/12/2025 Books
Withdrawn after missing   Dewey Decimal Classification   Not For Loan Library, Independent University, Bangladesh (IUB) Library, Independent University, Bangladesh (IUB) Reference Stacks 24/12/2025 Purchase 1575.00 2022   006.31 E368l 029521 18/01/2026 02 3150.00 24/12/2025 Books