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Machine Learning with R
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Solvereal-worlddataproblemswithRandmachinelearningKeyFeatures*Thirdeditionofthebestselling,widelyacclaimedRmachinelearningbook,updatedandimprovedforR3.6andbeyond*HarnessthepowerofRtobuildflexible,effective,andtransparentmachinelearningmodels*Learnquicklywithaclear,hands-onguidebyexperiencedmachinelearningteacherandpractitioner,BrettLantzBookDescriptionMachinelearning,atitscore,isconcernedwithtransformingdataintoactionableknowledge.Roffersapowerfulsetofmachinelearningmethodstoquicklyandeasilygaininsightfromyourdata.MachineLearningwithR,ThirdEditionprovidesahands-on,readableguidetoapplyingmachinelearningtoreal-worldproblems.WhetheryouareanexperiencedRuserornewtothelanguage,BrettLantzteachesyoueverythingyouneedtouncoverkeyinsights,makenewpredictions,andvisualizeyourfindings.Thisnew3rdeditionupdatestheclassicRdatasciencebooktoR3.6withnewerandbetterlibraries,adviceonethicalandbiasissuesinmachinelearning,andanintroductiontodeeplearning.Findpowerfulnewinsightsinyourdata;discovermachinelearningwithR.Whatyouwilllearn*Discovertheoriginsofmachinelearningandhowexactlyacomputerlearnsbyexample*PrepareyourdataformachinelearningworkwiththeRprogramminglanguage*ClassifyimportantoutcomesusingnearestneighborandBayesianmethods*Predictfutureeventsusingdecisiontrees,rules,andsupportvectormachines*Forecastnumericdataandestimatefinancialvaluesusingregressionmethods*Modelcomplexprocesseswithartificialneuralnetworks—thebasisofdeeplearning*Avoidbiasinmachinelearningmodels*Evaluateyourmodelsandimprovetheirperformance*ConnectRtoSQLdatabasesandemergingbigdatatechnologiessuchasSpark,H2O,andTensorFlowWhothisbookisforDatascientists,students,andotherpractitionerswhowantaclear,accessibleguidetomachinelearningwithR.

Brett Lantz ·自動化 ·12.1萬字

Windows Server 2019 Automation with PowerShell Cookbook
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AutomateWindowsservertaskswiththepowerfulfeaturesofthePowerShellLanguageKeyFeatures*LeveragePowerShelltoautomatecomplexWindowsservertasks*MasternewfeaturessuchasDevOps,andcontainers,andspeeduptheirperformanceusingPowerShell*ImprovePowerShell'susability,andcontrolandmanageWindows-basedenvironmentsbyworkingthroughexcitingrecipesBookDescriptionWindowsServer2019representsthelatestversionofMicrosoft’sflagshipserveroperatingsystem.ItalsocomeswithPowerShellVersion5.1andhasanumberofadditionalfeaturesthatITprosfinduseful.ThebookhelpsthereaderlearnhowtousePowerShellandmanagecoreroles,features,andservicesofWindowsServer2019.YouwillbeginwithcreatingaPowerShellAdministrativeEnvironmentthathasupdatedversionsofPowerShellandtheWindowsManagementFramework,updatedversionsofthe.NETFramework,andthird-partymodules.Next,youwilllearntousePowerShelltosetupandconfigureWindowsServer2019networkingandalsomanagingobjectsintheADenvironment.Youwillalsolearntosetupahosttoutilizecontainersandhowtodeploycontainers.YouwillalsobeimplementingdifferentmechanismsforachievingdesiredstateconfigurationalongwithgettingwellversedwithAzureinfrastructureandhowtosetupVirtualMachines,websites,andsharedfilesonAzure.Finally,youwillbeusingsomepowerfultoolsyoucanusetodiagnoseandresolveissueswithWindowsServer2019.Bytheendofthebook,youwilllearnalotoftripsandtrickstoautomateyourwindowsenvironmentwithPowerShellWhatyouwilllearn*PerformkeyadmintasksonWindowsServer2019*EmployingbestpracticesforwritingPowerShellscriptsandconfiguringWindowsServer2019*Usethe.NETFrameworktoachieveadministrativescripting*SetupVMs,websites,andsharedfilesonAzure*Reportsystemperformanceusingbuilt-incmdletsandWMItoobtainsinglemeasurements*KnowthetoolsyoucanusetodiagnoseandresolveissueswithWindowsServerWhothisbookisforIfyouareasystemsadministrator,engineer,oranarchitectworkingwithWindowsServer2016interestedinupgradingtoWindowsServer2019andautomatingtaskswithPowerShell,thenthisbookisforyou.AbasicknowledgeofPowerShellisexpected.

Thomas Lee ·自動化 ·9.3萬字

大數(shù)據(jù)平臺異常檢測分析系統(tǒng)的若干關(guān)鍵技術(shù)研究
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大數(shù)據(jù)技術(shù)生態(tài)體系中的各類技術(shù)構(gòu)件本身沒有可自省的安全機制,構(gòu)件間使用的RPC協(xié)議也沒有安全機制,大數(shù)據(jù)平臺的安全性面臨著巨大挑戰(zhàn),如何高效、快速地檢測大數(shù)據(jù)平臺中的應(yīng)用異常對提高大數(shù)據(jù)平臺的安全性具有重要意義。本書在介紹相關(guān)研究工作及相關(guān)基礎(chǔ)內(nèi)容之后,主要針對大數(shù)據(jù)平臺的應(yīng)用層日志數(shù)據(jù),研究了平臺異常的檢測與分析問題,構(gòu)建了大數(shù)據(jù)平臺異常的離線檢測分析的方法體系及實時檢測的機制。研究了基于數(shù)據(jù)流二重概念漂移檢測的增量學(xué)習(xí)、分布式日志的最大頻繁序列模式挖掘算法、基于最大頻繁模式的動態(tài)規(guī)則庫構(gòu)建算法、基于Web會話流的分布式實時異常定位算法、基于最大信息系數(shù)的在線異常檢測算法、基于聚類分析的離線異常檢測算法、基于相鄰請求的動態(tài)時間閾值會話識別算法、基于會話特征相似性模糊聚類的SFAD異常檢測算法、基于貝葉斯粒子群的異常檢測算法、平臺異常時的推測式任務(wù)調(diào)度策略、基于實時負(fù)載的推測式任務(wù)調(diào)度算法。分析了大數(shù)據(jù)平臺異常檢測分析(RADA)系統(tǒng)在實現(xiàn)時所采用的大數(shù)據(jù)技術(shù)與組件技術(shù)選型,針對RADA系統(tǒng)進行了深入的結(jié)構(gòu)化分析,介紹了基于融合架構(gòu)的RADA系統(tǒng)概要設(shè)計,研究了RADA系統(tǒng)的詳細(xì)設(shè)計與實現(xiàn)方法,完整地總結(jié)了大數(shù)據(jù)平臺異常的實時檢測技術(shù)與分析RADA系統(tǒng)的關(guān)鍵技術(shù)。

肖如良 ·自動化 ·12.6萬字

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