15 Probabilistic Machine Learning

书名：ProbabilisticMachineLearning 作者：KevinP.Murphy 出版社：TheMITPress 译者： 出版日期：2022-3 页数：864 ISBN：9780262046824

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书籍简介：

Adetailedandup-to-dateintroductiontomachinelearning,presentedthroughtheunifyinglensofprobabilisticmodelingandBayesiandecisiontheory.

Thisbookoffersadetailedandup-to-dateintroductiontomachinelearning(includingdeeplearning)throughtheunifyinglensofprobabilisticmodelingandBayesiandecisiontheory.Thebookcoversmathematicalbackground(includinglinearalgebraandoptimization),basicsupervisedlearning(includinglinearandlogisticregressionanddeepneuralnetworks),aswellasmoreadvancedtopics(includingtransferlearningandunsupervisedlearning).End-of-chapterexercisesallowstudentstoapplywhattheyhavelearned,andanappendixcoversnotation.

ProbabilisticMachineLearninggrewoutoftheauthor’s2012book,MachineLearning:AProbabilisticPerspective.Morethanjustasimpleupdate,thisisacompletelynewbookthatreflectsthedramaticdevelopmentsinthefieldsince2012,mostnotablydeeplearning.Inaddition,thenewbookisaccompaniedbyonlinePythoncode,usinglibrariessuchasscikit-learn,JAX,PyTorch,andTensorflow,whichcanbeusedtoreproducenearlyallthefigures;thiscodecanberuninsideawebbrowserusingcloud-basednotebooks,andprovidesapracticalcomplementtothetheoreticaltopicsdiscussedinthebook.Thisintroductorytextwillbefollowedbyasequelthatcoversmoreadvancedtopics,takingthesameprobabilisticapproach.