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Introduction to machine learning / (Record no. 665611)

MARC details
000 -LEADER
fixed length control field	02143cam a2200193 i 4500
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN	9780262043793
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number	006.31
Edition number	23
Item number	ALP
084 ## - OTHER CLASSIFICATION NUMBER
Source of Number	Colon Classification
100 1# - MAIN ENTRY--AUTHOR NAME
Personal name	Alpaydin, Ethem,
245 10 - TITLE STATEMENT
Title	Introduction to machine learning /
Statement of responsibility, etc	Ethem Alpaydin.
250 ## - EDITION STATEMENT
Edition statement	Fourth edition.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication	Cambridge:
Name of publisher	The MIT Press,
Year of publication	2020.
300 ## - PHYSICAL DESCRIPTION
Number of Pages	xxiv, 682 pages :
Other physical details	illustrations ;
490 0# - SERIES STATEMENT
Series statement	Adaptive computation and machine learning series
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc	Includes bibliographical references and index.
520 ## - SUMMARY, ETC.
Summary, etc	"Since the third edition of this text appeared in 2014, most recent advances in machine learning, both in theory and application, are related to neural networks and deep learning. In this new edition, the author has extended the discussion of multilayer perceptrons. He has also added a new chapter on deep learning including training deep neural networks, regularizing them so they learn better, structuring them to improve learning, e.g., through convolutional layers, and their recurrent extensions with short-term memory necessary for learning sequences. There is a new section on generative adversarial networks that have found an impressive array of applications in recent years. Alpaydin has also extended the chapter on reinforcement learning to discuss the use of deep networks in reinforcement learning. There is a new section on the policy gradient method that has been used frequently in recent years with neural networks, and two additional sections on two examples of deep reinforcement learning, which both made headlines when they were announced in 2015 and 2016 respectively. One is a network that learns to play arcade video games, and the other one learns to play Go. There are also revisions in other chapters reflecting new approaches, such as embedding methods for dimensionality reduction, and multi-label classification. In response to requests from instructors, this new edition contains two new appendices on linear algebra and optimization, to remind the reader of the basics of those topics that find use in machine learning"--
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term	Machine learning.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type	Book

Holdings
Collection code	Home Library	Current Location	Shelving location	Date acquired	Full call number	Accession Number	Price effective from	Koha item type	Source of classification or shelving scheme	Copy number	Public note
Non-fiction	Dept. of Futures Studies	Dept. of Futures Studies	General Stacks	29/11/2022	006.31 ALP;1	DFS4506	29/11/2022	Book
	Dept. of Optoelectronics	Dept. of Optoelectronics	New Materials Shelf	29/01/2024	006.31 ALP/M	DOP3673	29/01/2024	Book	Dewey Decimal Classification
	Dept. of Optoelectronics	Dept. of Optoelectronics	New Materials Shelf	29/01/2024	006.31 ALP/M;1	DOP3746	29/01/2024	Book	Dewey Decimal Classification	1	Reference Only
	Dept. of Optoelectronics	Dept. of Optoelectronics	New Materials Shelf	08/10/2025	006.31 ALP/M;2	DOP3747	08/10/2025	Book	Dewey Decimal Classification		Reference Only
	Dept. of Optoelectronics	Dept. of Optoelectronics	New Materials Shelf	08/10/2025	006.31 ALP/M;3	DOP3748	08/10/2025	Book	Dewey Decimal Classification		Reference Only
	Dept. of Optoelectronics	Dept. of Optoelectronics	New Materials Shelf	08/10/2025	006.31 ALP/M;4	DOP3749	08/10/2025	Book	Dewey Decimal Classification		Reference Only
	Dept. of Optoelectronics	Dept. of Optoelectronics	New Materials Shelf	08/10/2025	006.31 ALP/M;5	DOP3750	08/10/2025	Book	Dewey Decimal Classification		Reference Only