東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Deep learning = a beginners' guide /

Meedeniya, Dulani.

Linked to FindBook

Google Book

Amazon

博客來

Deep learning = a beginners' guide /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Deep learning/ Dulani Meedeniya.
Reminder of title:	a beginners' guide /
Author:	Meedeniya, Dulani.
Published:	Boca Raton, FL :Chapman & Hall/CRC Press, : 2024.,
Description:	1 online resource (184 p.) :ill.
[NT 15003449]:	1. Introduction. 2. Concepts and Terminology. 3. State-of-the-Art Deep Learning Models: Part I. 4. State-of-the-Art Deep Learning Models: Part II. 5. Advanced Learning Techniques. 6. Enhancement of Deep Learning Architectures. 7. Performance Evaluation Techniques.
Subject:	Deep learning (Machine learning) -
Online resource:	https://www.taylorfrancis.com/books/9781003390824
ISBN:	9781003390824

Deep learning = a beginners' guide /
Meedeniya, Dulani.

Deep learninga beginners' guide /[electronic resource] :Dulani Meedeniya. - 1st ed. - Boca Raton, FL :Chapman & Hall/CRC Press,2024. - 1 online resource (184 p.) :ill.

Includes bibliographical references and index.

1. Introduction. 2. Concepts and Terminology. 3. State-of-the-Art Deep Learning Models: Part I. 4. State-of-the-Art Deep Learning Models: Part II. 5. Advanced Learning Techniques. 6. Enhancement of Deep Learning Architectures. 7. Performance Evaluation Techniques.

This book focuses on deep learning (DL), which is an important aspect of data science, that includes predictive modeling. DL applications are widely used in domains such as finance, transport, healthcare, automanufacturing, and advertising. The design of the DL models based on artificial neural networks is influenced by the structure and operation of the brain. This book presents a comprehensive resource for those who seek a solid grasp of the techniques in DL. Key features: Provides knowledge on theory and design of state-of-the-art deep learning models for real-world applications Explains the concepts and terminology in problem-solving with deep learning Explores the theoretical basis for major algorithms and approaches in deep learning Discusses the enhancement techniques of deep learning models Identifies the performance evaluation techniques for deep learning models Accordingly, the book covers the entire process flow of deep learning by providing awareness of each of the widely used models. This book can be used as a beginners' guide where the user can understand the associated concepts and techniques. This book will be a useful resource for undergraduate and postgraduate students, engineers, and researchers, who are starting to learn the subject of deep learning.

ISBN: 9781003390824Subjects--Topical Terms:

3538509
Deep learning (Machine learning)

LC Class. No.: Q325.73

Dewey Class. No.: 006.31

Deep learning = a beginners' guide /
LDR:02721cmm a2200361 a 4500 001 2416423
005 20251017072503.0
006 m o d
007 cr cnu---unuuu
008 260303s2024 flua ob 001 0 eng d
020 $a 9781003390824 $q (electronic bk.)
020 $a 100339082X $q (electronic bk.)
020 $a 9781000924060 $q (ePub ebook)
020 $a 1000924068 $q (ePub ebook)
020 $a 9781000924053 $q (electronic bk. : PDF)
020 $a 100092405X $q (electronic bk. : PDF)
020 $z 9781032487960 $q (pbk.)
020 $z 9781032473246 $q (hbk.)
035 $a (OCoLC)1400792559
035 $a (OCoLC-P)1400792559
035 $a 9781003390824
040 $a OCoLC-P $b eng $c OCoLC-P
041 0 $a eng
050 4 $a Q325.73
082 0 4 $a 006.31 $2 23
100 1 $a Meedeniya, Dulani. $3 3795121
245 1 0 $a Deep learning $h [electronic resource] : $b a beginners' guide / $c Dulani Meedeniya.
250 $a 1st ed.
260 $a Boca Raton, FL : $b Chapman & Hall/CRC Press, $c 2024.
300 $a 1 online resource (184 p.) : $b ill.
504 $a Includes bibliographical references and index.
505 0 $a 1. Introduction. 2. Concepts and Terminology. 3. State-of-the-Art Deep Learning Models: Part I. 4. State-of-the-Art Deep Learning Models: Part II. 5. Advanced Learning Techniques. 6. Enhancement of Deep Learning Architectures. 7. Performance Evaluation Techniques.
520 $a This book focuses on deep learning (DL), which is an important aspect of data science, that includes predictive modeling. DL applications are widely used in domains such as finance, transport, healthcare, automanufacturing, and advertising. The design of the DL models based on artificial neural networks is influenced by the structure and operation of the brain. This book presents a comprehensive resource for those who seek a solid grasp of the techniques in DL. Key features: Provides knowledge on theory and design of state-of-the-art deep learning models for real-world applications Explains the concepts and terminology in problem-solving with deep learning Explores the theoretical basis for major algorithms and approaches in deep learning Discusses the enhancement techniques of deep learning models Identifies the performance evaluation techniques for deep learning models Accordingly, the book covers the entire process flow of deep learning by providing awareness of each of the widely used models. This book can be used as a beginners' guide where the user can understand the associated concepts and techniques. This book will be a useful resource for undergraduate and postgraduate students, engineers, and researchers, who are starting to learn the subject of deep learning.
588 $a OCLC-licensed vendor bibliographic record.
650 0 $a Deep learning (Machine learning) $3 3538509
856 4 0 $u https://www.taylorfrancis.com/books/9781003390824