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

Machine learning = theoretical found...

Pandey, Manjusha.

Linked to FindBook

Google Book

Amazon

博客來

Machine learning = theoretical foundations and practical applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning/ edited by Manjusha Pandey, Siddharth Swarup Rautaray.
Reminder of title:	theoretical foundations and practical applications /
other author:	Pandey, Manjusha.
Published:	Singapore :Springer Singapore : : 2021.,
Description:	xi, 172 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Chapter 1. What do RDMs capture in Brain Responses and Computational Models? -- Chapter 2. Challenges and solutions, in developing Convolutional Neural Networks and Long Short Term Memory networks, for industry problems -- Chapter 3. Speed, Cloth and Pose Invariant Gait recognition Based Person Identifification -- Chapter 4. Applications of Machine learning in industry 4.0 -- Chapter 5. Web Semantics and Knowledge Graph -- Chapter 6. Machine Learning based Wireless Sensor Networks -- Chapter 7. AI to Machine Learning:lifeless automation and Issues -- Chapter 8. Analysis of FDIs in Different Sectors of the Indian Economy -- Chapter 9. Customer Profiling & Retention using Recommendation system and Factor Identification to predict Customer Chur In Telecom Industry.
Contained By:	Springer Nature eBook
Subject:	Machine learning - Congresses. -
Online resource:	https://doi.org/10.1007/978-981-33-6518-6
ISBN:	9789813365186

Machine learning = theoretical foundations and practical applications /
Machine learningtheoretical foundations and practical applications /[electronic resource] :edited by Manjusha Pandey, Siddharth Swarup Rautaray. - Singapore :Springer Singapore :2021. - xi, 172 p. :ill. (some col.), digital ;24 cm. - Studies in big data,v.872197-6503 ;. - Studies in big data ;v.87..

Chapter 1. What do RDMs capture in Brain Responses and Computational Models? -- Chapter 2. Challenges and solutions, in developing Convolutional Neural Networks and Long Short Term Memory networks, for industry problems -- Chapter 3. Speed, Cloth and Pose Invariant Gait recognition Based Person Identifification -- Chapter 4. Applications of Machine learning in industry 4.0 -- Chapter 5. Web Semantics and Knowledge Graph -- Chapter 6. Machine Learning based Wireless Sensor Networks -- Chapter 7. AI to Machine Learning:lifeless automation and Issues -- Chapter 8. Analysis of FDIs in Different Sectors of the Indian Economy -- Chapter 9. Customer Profiling & Retention using Recommendation system and Factor Identification to predict Customer Chur In Telecom Industry.

This edited book is a collection of chapters invited and presented by experts at 10th industry symposium held during 9-12 January 2020 in conjunction with 16th edition of ICDCIT. The book covers topics, like machine learning and its applications, statistical learning, neural network learning, knowledge acquisition and learning, knowledge intensive learning, machine learning and information retrieval, machine learning for web navigation and mining, learning through mobile data mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory, cognitive modelling and hybrid learning algorithms.

ISBN: 9789813365186

Standard No.: 10.1007/978-981-33-6518-6doiSubjects--Topical Terms:

576368
Machine learning
--Congresses.

LC Class. No.: Q325.5 / .M334 2021

Dewey Class. No.: 006.31

Machine learning = theoretical foundations and practical applications /
LDR:02659nmm a2200337 a 4500 001 2240004
003 DE-He213
005 20210729113829.0
006 m d
007 cr nn 008maaau
008 211111s2021 si s 0 eng d
020 $a 9789813365186 $q (electronic bk.)
020 $a 9789813365179 $q (paper)
024 7 $a 10.1007/978-981-33-6518-6 $2 doi
035 $a 978-981-33-6518-6
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5 $b .M334 2021
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .M149 2021
245 0 0 $a Machine learning $h [electronic resource] : $b theoretical foundations and practical applications / $c edited by Manjusha Pandey, Siddharth Swarup Rautaray.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2021.
300 $a xi, 172 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in big data, $x 2197-6503 ; $v v.87
505 0 $a Chapter 1. What do RDMs capture in Brain Responses and Computational Models? -- Chapter 2. Challenges and solutions, in developing Convolutional Neural Networks and Long Short Term Memory networks, for industry problems -- Chapter 3. Speed, Cloth and Pose Invariant Gait recognition Based Person Identifification -- Chapter 4. Applications of Machine learning in industry 4.0 -- Chapter 5. Web Semantics and Knowledge Graph -- Chapter 6. Machine Learning based Wireless Sensor Networks -- Chapter 7. AI to Machine Learning:lifeless automation and Issues -- Chapter 8. Analysis of FDIs in Different Sectors of the Indian Economy -- Chapter 9. Customer Profiling & Retention using Recommendation system and Factor Identification to predict Customer Chur In Telecom Industry.
520 $a This edited book is a collection of chapters invited and presented by experts at 10th industry symposium held during 9-12 January 2020 in conjunction with 16th edition of ICDCIT. The book covers topics, like machine learning and its applications, statistical learning, neural network learning, knowledge acquisition and learning, knowledge intensive learning, machine learning and information retrieval, machine learning for web navigation and mining, learning through mobile data mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory, cognitive modelling and hybrid learning algorithms.
650 0 $a Machine learning $x Congresses. $3 576368
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Machine Learning. $3 3382522
650 2 4 $a Communications Engineering, Networks. $3 891094
700 1 $a Pandey, Manjusha. $3 3489788
700 1 $a Rautaray, Siddharth Swarup. $3 3446107
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Studies in big data ; $v v.87. $3 3494575
856 4 0 $u https://doi.org/10.1007/978-981-33-6518-6
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)