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Deep learning :from big data to artificial intelligence with R /

紀錄類型:	書目-語言資料,印刷品 : 單行本
正題名/作者:	Deep learning :/ Stéphane Tufféry.
其他題名:	from big data to artificial intelligence with R /
作者:	Tuffery, Stéphane.
出版者:	Chichester, West Sussex, UK :Wiley,c2023.
面頁冊數:	xix, 519 p. :ill. ;26 cm.
標題:	Deep learning (Machine learning) -
ISBN:	9781119845010
ISBN:	9781119845027
ISBN:	9781119845034

Deep learning :from big data to artificial intelligence with R /
Tuffery, Stéphane.

Deep learning :from big data to artificial intelligence with R /Stéphane Tufféry. - Chichester, West Sussex, UK :Wiley,c2023. - xix, 519 p. :ill. ;26 cm.

Includes bibliographical references (p. 507-513) and index.

"Deep learning is a class of machine learning algorithms that uses multiple layers to progressively extract higher-level features from the raw input. Deep-learning architectures such as deep neural networks, deep belief networks, recurrent neural networks and convolutional neural networks have been applied to fields including computer vision, machine vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, bioinformatics, drug design, medical image analysis, material inspection and board game programs, where they have produced results comparable to and in some cases surpassing human expert performance. Deep learning is at the heart of artificial intelligence and achievements and errors in the field are driving a great and constant interest"--

ISBN: 9781119845010NT2569

LCCN: 2022049572Subjects--Topical Terms:

1000148112
Deep learning (Machine learning)

LC Class. No.: Q325.73 / .T84 2023

Dewey Class. No.: 006.3/1

Deep learning :from big data to artificial intelligence with R /
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520 # $a "Deep learning is a class of machine learning algorithms that uses multiple layers to progressively extract higher-level features from the raw input. Deep-learning architectures such as deep neural networks, deep belief networks, recurrent neural networks and convolutional neural networks have been applied to fields including computer vision, machine vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, bioinformatics, drug design, medical image analysis, material inspection and board game programs, where they have produced results comparable to and in some cases surpassing human expert performance. Deep learning is at the heart of artificial intelligence and achievements and errors in the field are driving a great and constant interest"-- $c Provided by publisher.
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650 # 0 $a R (Computer program language) $3 177289
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