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006			m |o d |
007			cr_|||||||||||
008			230125t20232023nju ob 001 0 eng c
010			_a 2023003263
020			_a9781119897620 _q(pdf)
020			_z9781119897606 _q(hardback)
040			_aDLC _beng _cDLC _erda
042			_apcc
050	0	0	_aQ325.5
082	0	0	_a006.3/1 _223/eng20230506
100	1		_aNaser, M. Z., _eauthor. _9128629
245	1	0	_aMachine learning for civil & environmental engineers : _ba practical approach to data-driven analysis, explainability, and causality / _cM. Z. Naser.
263			_a2305
264		1	_aHoboken, New Jersey : _bWiley, _c[2023]
264		4	_c©2023
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
504			_aIncludes bibliographical references and index.
520			_a"Synopsis: The theme of this textbook revolves around how machine learning (ML) can help civil and environmental engineers transform their domain. This textbook hopes to deliver the knowledge and information necessary to educate engineering students and practitioners on the principles of ML and how to integrate these into our field. This textbook is about navigating the realm of data-driven ML, explainable ML, and causal ML from the context of education, research, and practice. In hindsight, this textbook augments ML into the heart of engineering. Together, we will go over the big ideas behind ML. We will ask and answer questions such as, what is ML? Why is ML needed? How does ML differ from statistics, physical testing, and numerical simulation? Can we trust ML? And how can we benefit from ML, adapt to it, adopt it, wield it, and leverage it to overcome many, many of the problems that we may face? This book is also about showing you, my dear reader, how to amplify your engineering knowledge with a new tool. A tool that is yet to be formally taught in our curriculum. A tool that many civil and environmental engineering departments and schools may not fully appreciate ; yet are eager to know more about!"-- _cProvided by publisher.
588			_aDescription based on print version record and CIP data provided by publisher; resource not viewed.
590			_6.
650		0	_aMachine learning.
650		0	_aCivil engineering _xData processing. _9128630
650		0	_aEnvironmental engineering _xData processing. _9128631
710	2		_aJohn Wiley & Sons, _epublisher. _996141
776	0	8	_iPrint version: _aNaser, M. Z. _tMachine learning for civil & environmental engineers _dHoboken, New Jersey : Wiley, [2023] _z9781119897606 _w(DLC) 2023003262
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK
999			_c613537 _d613537