000			02179nam a22003618i 4500
001			CR9781139164542
003			UkCbUP
005			20200124160301.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			111007s2001||||enk o ||1 0|eng|d
020			_a9781139164542 (ebook)
020			_z9780521773072 (hardback)
020			_z9780521774796 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQA76.87 _b.E45 2001
082	0	0	_a006.3 _221
100	1		_aEngel, A. _q(Andreas), _d1957- _eauthor.
245	1	0	_aStatistical mechanics of learning / _cA. Engel, C. van den Broeck.
264		1	_aCambridge : _bCambridge University Press, _c2001.
300			_a1 online resource (xi, 329 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
520			_aLearning is one of the things that humans do naturally, and it has always been a challenge for us to understand the process. Nowadays this challenge has another dimension as we try to build machines that are able to learn and to undertake tasks such as datamining, image processing and pattern recognition. We can formulate a simple framework, artificial neural networks, in which learning from examples may be described and understood. The contribution to this subject made over the last decade by researchers applying the techniques of statistical mechanics is the subject of this book. The authors provide a coherent account of various important concepts and techniques that are currently only found scattered in papers, supplement this with background material in mathematics and physics and include many examples and exercises to make a book that can be used with courses, or for self-teaching, or as a handy reference.
650		0	_aNeural networks (Computer science)
650		0	_aLearning.
650		0	_aArtificial intelligence.
700	1		_aBroeck, C. van den _q(Christian), _d1954- _eauthor.
776	0	8	_iPrint version: _z9780521773072
856	4	0	_uhttps://doi.org/10.1017/CBO9781139164542
999			_c520405 _d520403