000			00967 a2200157 4500
005			20250526100128.0
020			_a978-0262046824
082			_a006.31 _bMUR-P
100			_aMurphy, Kevin P.
245			_aProbabilistic Machine Learning : _bAn Introduction /
260			_aLondon: _bThe MIT Press, _c2022.
300			_axxix, 823p _c21cm x 28cm
500			_aIncludes bibliography.
650			_aThis book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation.
942			_cBK
999			_c34964 _d34964