000			02092cam a22003858i 4500
001			22338243
003			OSt
005			20240823102700.0
008			211208s2022 flu b 001 0 eng
010			_a 2021059529
020			_a9780367771652 _q(hardback)
020			_a9780367767341 _q(paperback)
020			_z9781003170082 _q(ebook)
040			_aDLC _beng _erda _cRLKU
042			_apcc
050	0	0	_aQA76.87 _b.K354 2022
082	0	0	_a005 _223/eng/20220218
100	1		_aKamath, Uday, _eauthor. _9608
245	1	0	_aTransformers for machine learning : _ba deep dive / _cUday Kamath, Kenneth Graham, Wael Emara.
250			_aFirst edition.
263			_a2205
264		1	_aBoca Raton : _bCRC Press, _c2022.
300			_apages cm
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references and index.
520			_a"Transformers are becoming a core part of many neural network architectures, employed in a wide range of applications such as NLP, Speech Recognition, Time Series, and Computer Vision. Transformers have gone through many adaptations and alterations, resulting in newer techniques and methods. Transformers for Machine Learning: A Deep Dive is the first comprehensive book on transformers. The theoretical explanations of the state-of-the-art transformer architectures will appeal to postgraduate students and researchers (academic and industry) as it will provide a single entry point with deep discussions of a quickly moving field. The practical hands-on case studies and code will appeal to undergraduate students, practitioners, and professionals as it allows for quick experimentation and lowers the barrier to entry into the field"-- _cProvided by publisher.
650		0	_aNeural networks (Computer science). _9609
650		0	_aComputational intelligence. _9610
650		0	_aMachine learning. _9521
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK _n0
999			_c18082 _d18082