Deep learning (Record no. 6710)

MARC details
000 -LEADER
fixed length control field 02237nam a22001937a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240227201854.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240227b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780262537551
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Item number KEL
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Kelleher, John D.
245 ## - TITLE STATEMENT
Title Deep learning
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc. The MIT Press
Place of publication, distribution, etc. Cambridge
Date of publication, distribution, etc. 2019
300 ## - PHYSICAL DESCRIPTION
Extent x, 280 p.
365 ## - TRADE PRICE
Price type code USD
Price amount 15.95
520 ## - SUMMARY, ETC.
Summary, etc. An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars.<br/><br/>Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications. When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution.<br/><br/>Kelleher explains that deep learning enables data-driven decisions by identifying and extracting patterns from large datasets; its ability to learn from complex data makes deep learning ideally suited to take advantage of the rapid growth in big data and computational power. Kelleher also explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art. He describes the most important deep learning architectures, including autoencoders, recurrent neural networks, and long short-term networks, as well as such recent developments as Generative Adversarial Networks and capsule networks. He also provides a comprehensive (and comprehensible) introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the future of deep learning—major trends, possible developments, and significant challenges.<br/><br/>(https://mitpress.mit.edu/9780262537551/deep-learning/)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Book
Source of classification or shelving scheme Dewey Decimal Classification
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Bill No Bill Date Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Serial Enumeration / chronology Total Checkouts Total Renewals Full call number Accession Number Date last seen Date checked out Copy number Cost, replacement price Price effective from Koha item type
    Dewey Decimal Classification     IT & Decisions Sciences TB3913 22-02-2024 Indian Institute of Management LRC Indian Institute of Management LRC General Stacks 02/27/2024 Technical Bureau India Pvt. Ltd. 896.79 1 2 2 006.31 KEL 006278 10/17/2024 09/20/2024 1 1379.68 02/27/2024 Book

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