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上传时间:2023/7/11 7:13:56
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Machine.Learning.The.New.AI.pdf
Today,machinelearningunderliesarangeofapplicationsweuseeveryday,fromproductrecommendationstovoicerecognition--aswellassomewedon'tyetuseeveryday,includingdriverlesscars.Itisthebasisofthenewapproachincomputingwherewedonotwriteprogramsbutcollectdata;theideaistolearnthealgorithmsforthetasksautomaticallyfromdata.Ascomputingdevicesgrowmoreubiquitous,alargerpartofourlivesandworkisrecordeddigitally,andas"BigData"hasgottenbigger,thetheoryofmachinelearning--thefoundationofeffortstoprocessthatdataintoknowledge--hasalsoadvanced.Inthisbook,machinelearningexpertEthemAlpaydinoffersaconciseoverviewofthesubjectforthegeneralreader,describingitsevolution,explainingimportantlearningalgorithms,andpresentingexampleapplications.Alpaydinoffersanaccountofhowdigitaltechnologyadvancedfromnumber-crunchingmainframestomobiledevices,puttingtoday'smachinelearningboomincontext.Hedescribesthebasicsofmachinelearningandsomeapplications;theuseofmachinelearningalgorithmsforpatternrecognition;artificialneuralnetworksinspiredbythehumanbrain;algorithmsthatlearnassociationsbetweeninstances,withsuchapplicationsascustomersegmentationandlearningrecommendations;andreinforcementlearning,whenanautonomousagentlearnsactsoastomaximizerewardandminimizepenalty.Alpaydinthenconsiderssomefuturedirectionsformachinelearningandthenewfieldof"datascience,"anddiscussestheethicalandlegalimplicationsfordataprivacyandsecurity.TableofContentsChapter1WhyWeAreInterestedInMachineLearningChapter2MachineLearning,Statistics,AndDataAnalyticsChapter3PatternRecognitionChapter4NeuralNetworksAndDeepLearningChapter5LearningClustersAndRecommendationsChapter6LearningToTakeActionsChapter7WhereDoWeGoFromHere?
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