000			02245cam a22002538i 4500
001			10867
003			IN-BhIIT
005			20240626174319.0
008			210805s2021 enk b 001 0 eng
020			_a9781108940023
040			_aIN-BhIIT
041			_aeng
082	0	0	_a006.31 _bJIA/M
100	1		_aJiang, Hui _eAuthor. _923574
245	1	0	_aMachine learning fundamentals : _ba concise introduction / _cby Hui Jiang.
260			_aNew Delhi : _bCambridge University Press, _c2021.
300			_axv, 380 p. : _bill. ; _c24 cm.
504			_aIncludes bibliographical references and index.
520			_a"This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely "from scratch" based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts. Hui Jiang is Professor of Electrical Engineering and Computer Science at York University, where he has been since 2002. His main research interests include machine learning, particularly deep learning, and its applications to speech and audio processing, natural language processing, and computer vision. Over the past 30 years, he has worked on a wide range of research problems from these areas and published hundreds of technical articles and papers in the mainstream journals and top-tier conferences. His works have won the prestigious IEEE Best Paper Award and the ACL Outstanding Paper honor"--
650		0	_aMachine learning.
650		7	_aArtificial Intelligence. _9739
650		7	_aComputer Vision and Pattern Recognition. _923575
942			_cTRB
999			_c13845 _d13845