000			02327nam a2200325Ia 4500
003			OSt
005			20250410020503.0
008			240709s9999 xx 000 0 und d
020			_a9781493938438 (pbk.) _c€ 74.99
040			_bENG _cIISER-BPR
041			_aENG
082			_a006.31 _bBIS _223rd
100			_aBishop, Christopher M. _9993
222			_aComputer Sciences
245		0	_aPattern recognition and machine learning
250			_a1st ed.
260			_aNew York: _bSpringer, _cc2006.
300			_axx, 738p. : _bill(col.). ; _c25cm.
440			_aInformation Science and Statistics _9994
504			_aIncludes colored illustrations, appendices, bibliographical references and index.
520			_aPattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation pro- gation. Similarly, new models based on kernels have had significant impact on both algorithms and applications. This new textbook reacts these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first year PhD students, as wellas researchers and practitioners, and assumes no previous knowledge of pattern recognition or - chine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
650			_aSpecial Computer Methods _9995
650			_aArtificial Intelligence _9996
650			_aPattern Recognition _9997
650			_aMachine Learning _9998
942			_cBK _2ddc _03
942			_2ddc
947			_a7645.7004
948			_a0.22
999			_c4110 _d4110