000			01414nam a22002057a 4500
005			20150131105649.0
008			141211b xxu||||| |||| 00| 0 eng d
020			_a9781490227634
050			_aLB 1044.87 _b.Sm645 2013
100			_aMurphy, Kevin P.
245			_aJust the facts101 Machine learning : _ba probabilistic perspective / _cKevin P. Murphy.
250			_a1st ed.
260			_bCram101 Publishing, _c2013.
300			_a260 pages ; _c28 cm.
440			_aJust the fact 101 study guide.
520			_aCram101 Textbook Outline notebooks have been designed so you can get the most out of your class and study time. The outlines consist of all the terms, concepts, places, people organisations and events that you may expect to be tested from your textbook. The purpose of the outline format is to speed up and increase your comprehension of the material. Machine learning : a probabilistic perspective offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning.
650			_aMachine learning.
650			_aProbabilities.
942			_2lcc _cBK _kFOR
999			_c276955 _d276955