Welding and Cutting Case Studies with Supervised Machine Learning (Record no. 77468)

000 -LEADER
fixed length control field 03948nam a22006255i 4500
001 - CONTROL NUMBER
control field 978-981-13-9382-2
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801215421.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 200603s2020 si | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9789811393822
-- 978-981-13-9382-2
082 04 - CLASSIFICATION NUMBER
Call Number 670
100 1# - AUTHOR NAME
Author Vendan, S. Arungalai.
245 10 - TITLE STATEMENT
Title Welding and Cutting Case Studies with Supervised Machine Learning
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2020.
300 ## - PHYSICAL DESCRIPTION
Number of Pages IX, 249 p. 257 illus., 192 illus. in color.
490 1# - SERIES STATEMENT
Series statement Engineering Applications of Computational Methods,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Supervised machine learning in magnetically impelled arc butt welding (MIAB) -- Supervised machine learning in cold metal transfer (CMT) -- Supervised machine learning in friction stir welding (FSW) -- Supervised machine learning in wire cut electric discharge maching (WEDM) -- Appendix: coding in python, numpy, panda, scikit-learn used for analysis with emphasis on libraries.
520 ## - SUMMARY, ETC.
Summary, etc This book presents machine learning as a set of pre-requisites, co-requisites, and post-requisites, focusing on mathematical concepts and engineering applications in advanced welding and cutting processes. It describes a number of advanced welding and cutting processes and then assesses the parametrical interdependencies of two entities, namely the data analysis and data visualization techniques, which form the core of machine learning. Subsequently, it discusses supervised learning, highlighting Python libraries such as NumPy, Pandas and Scikit Learn programming. It also includes case studies that employ machine learning for manufacturing processes in the engineering domain. The book not only provides beginners with an introduction to machine learning for applied sciences, enabling them to address global competitiveness and work on real-time technical challenges, it is also a valuable resource for scholars with domain knowledge.
700 1# - AUTHOR 2
Author 2 Kamal, Rajeev.
700 1# - AUTHOR 2
Author 2 Karan, Abhinav.
700 1# - AUTHOR 2
Author 2 Gao, Liang.
700 1# - AUTHOR 2
Author 2 Niu, Xiaodong.
700 1# - AUTHOR 2
Author 2 Garg, Akhil.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-981-13-9382-2
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Singapore :
-- Springer Nature Singapore :
-- Imprint: Springer,
-- 2020.
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-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Manufactures.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Machine learning.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering—Data processing.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Materials—Analysis.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Machines, Tools, Processes.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Machine Learning.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Characterization and Analytical Technique.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2662-3374 ;
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-- ZDB-2-ENG
912 ## -
-- ZDB-2-SXE

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