000			03078cam a2200481Mi 4500
001			9781003119258
003			FlBoTFG
005			20240213122831.0
006			m o d
007			cr |n|||||||||
008			220708s2022 flu ob 001 0 eng d
040			_aOCoLC-P _beng _cOCoLC-P
020			_a9781000737691 _q(electronic bk.)
020			_a1000737691 _q(electronic bk.)
020			_a9781003119258 _q(electronic bk.)
020			_a1003119255 _q(electronic bk.)
020			_a9781000737721 _q(electronic bk. : EPUB)
020			_a1000737721 _q(electronic bk. : EPUB)
020			_z9780367634537
020			_z0367634538
024	7		_a10.1201/9781003119258 _2doi
035			_a(OCoLC)1334658646
035			_a(OCoLC-P)1334658646
050		4	_aQ325.5
072		7	_aBUS _x061000 _2bisacsh
072		7	_aCOM _x037000 _2bisacsh
072		7	_aMAT _x004000 _2bisacsh
072		7	_aUYQ _2bicssc
082	0	4	_a006.3/1 _223/eng/20211216
100	1		_aMirtaheri, Seyedeh Leili, _d1980- _eauthor.
245	1	0	_aMachine learning _h[electronic resource] : _btheory to applications / _cSeyedeh Leili Mirtaheri, Assistant Professor, Electrical and Computer Engineering Department, Kharazmi University, Tehran, Reza Shahbazian, Department of Mathematics and Computer Science, University of Calabria, Italy.
250			_aFirst edition.
264		1	_aBoca Raton : _bCRC Press, _c2022.
300			_a1 online resource
520			_aThe book reviews core concepts of machine learning (ML) while focusing on modern applications. It is aimed at those who want to advance their understanding of ML by providing technical and practical insights. It does not use complicated mathematics to explain how to benefit from ML algorithms. Unlike the existing literature, this work provides the core concepts with emphasis on fresh ideas and real application scenarios. It starts with the basic concepts of ML and extends the concepts to the different deep learning algorithms. The book provides an introduction and main elements of evaluation tools with Python and walks you through the recent applications of ML in self-driving cars, cognitive decision making, communication networks, security, and signal processing. The concept of generative networks is also presented and focuses on GANs as a tool to improve the performance of existing algorithms. In summary, this book provides a comprehensive technological path from fundamental theories to the categorization of existing algorithms, covers state-of-the-art, practical evaluation tools and methods to empower you to use synthetic data to improve the performance of applications.
588			_aOCLC-licensed vendor bibliographic record.
650		7	_aBUSINESS & ECONOMICS / Statistics _2bisacsh
650		7	_aCOMPUTERS / Machine Theory _2bisacsh
650		7	_aMATHEMATICS / Arithmetic _2bisacsh
650		0	_aMachine learning.
856	4	0	_3Taylor & Francis _uhttps://www.taylorfrancis.com/books/9781003119258
856	4	2	_3OCLC metadata license agreement _uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
999			_c5830 _d5830