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ConfigurationManagement(CM)toolshelpadministratorsreducetheirworkload.AnsibleisoneofthebestConfigurationManagementtools,andcanactasanorchestratorformanagingotherCMs.ThisbookistheeasiestwaytolearnhowtouseAnsibleasanorchestratorandaConfigurationManagementtool.Withthisbook,youwilllearnhowtocontrolandmonitorcomputerandnetworkinfrastructuresofanysize,physicalorvirtual.YouwillbeginbylearningabouttheAnsibleclient-serverarchitecture.Togetstarted,youwillsetupandconfigureanAnsibleserver.YouwillthengothroughthemajorfeaturesofAnsible:PlaybookandInventory.Then,wewilllookatAnsiblesystemsandnetworkmodules.YouwillthenuseAnsibletoenableinfrastructureautomatedconfigurationmanagement,followedbybestpracticesforusingAnsiblerolesandcommunitymodules.Finally,youwillexploreAnsiblefeaturessuchasAnsibleVault,AnsibleContainers,andAnsibleplugins.

·3.9萬字

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HTML5 Canvas Cookbook

Writtenincookbookstyle,thisbookoffersawidearrayoftechniquesforbuildingHTML5Canvasapplications.Eachrecipecontainsstep-by-stepinstructionsfollowedbyanalysisofwhatwasdoneineachtaskandotherusefulinformation.Thebookisdesignedsothatyoucanreaditchapterbychapter,oryoucanlookatthelistofrecipesandrefertotheminnoparticularorder.ThisbookisgearedtowardswebdeveloperswhoarefamiliarwithHTMLandJavaScript.ItiswrittenforbothbeginnersandseasonedHTML5developerswithagoodworkingknowledgeofJavaScript.

·5.6萬字

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Redash v5 Quick Start Guide

DataexplorationandvisualizationisvitaltoBusinessIntelligence,thebackboneofalmosteveryenterpriseororganization.Redashisaqueryingandvisualizationtooldevelopedtosimplifyhowmarketingandbusinessdevelopmentdepartmentsareexposedtodata.IfyouwanttolearntocreateinteractivedashboardswithRedash,exploredifferentvisualizations,andsharetheinsightswithyourpeers,thenthisistheidealbookforyou.ThebookstartswithessentialBusinessIntelligenceconceptsthatareattheheartofdatavisualizations.YouwilllearnhowtofindyourwayroundRedashanditsricharrayofdatavisualizationoptionsforbuildinginteractivedashboards.Youwilllearnhowtocreatedatastorytellingandsharethesewithpeers.Youwillseehowtoconnecttodifferentdatasourcestoprocesscomplexdata,andthenvisualizethisdatatorevealvaluableinsights.Bytheendofthisbook,youwillbeconfidentwiththeRedashdashboardingtooltoprovideinsightandcommunicatedatastorytelling.

·2.9萬字

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WordPress for Education

WordPressforEducationisfullofscreenshots,practicalexamples,step-by-stepinstructions,andbestpracticesforusingWordPressinaneducationalsetting.WordPressforEducationiswrittenforeducatorsandeducationpersonnelinterestedinimplementingWordPressinaclassroomsetting.YouarenotrequiredtohavepreviousexperienceofWordPressoranyothercontentmanagementsystem.

·2.2萬字

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Practical Computer Vision

ThisbookisformachinelearningpractitionersanddeeplearningenthusiastswhowanttounderstandandimplementvarioustasksassociatedwithComputerVisionandimageprocessinginthemostpracticalmannerpossible.SomeprogrammingexperiencewouldbebeneficialwhileknowingPythonwouldbeanaddedbonus.

·4.1萬字

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Deep Learning Essentials

Aspiringdatascientistsandmachinelearningexpertswhohavelimitedornoexposuretodeeplearningwillfindthisbooktobeveryuseful.Ifyouarelookingforaresourcethatgetsyouupandrunningwiththefundamentalsofdeeplearningandneuralnetworks,thisbookisforyou.AsthemodelsinthebookaretrainedusingthepopularPython-basedlibrariessuchasTensorflowandKeras,itwouldbeusefultohavesoundprogrammingknowledgeofPython.

·6萬字

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Hands-On Artificial Intelligence for IoT

Therearemanyapplicationsthatusedatascienceandanalyticstogaininsightsfromterabytesofdata.Theseapps,however,donotaddressthechallengeofcontinuallydiscoveringpatternsforIoTdata.InHands-OnArtificialIntelligenceforIoT,wecovervariousaspectsofartificialintelligence(AI)anditsimplementationtomakeyourIoTsolutionssmarter.ThisbookstartsbycoveringtheprocessofgatheringandpreprocessingIoTdatagatheredfromdistributedsources.YouwilllearndifferentAItechniquessuchasmachinelearning,deeplearning,reinforcementlearning,andnaturallanguageprocessingtobuildsmartIoTsystems.YouwillalsoleveragethepowerofAItohandlereal-timedatacomingfromwearabledevices.Asyouprogressthroughthebook,techniquesforbuildingmodelsthatworkwithdifferentkindsofdatageneratedandconsumedbyIoTdevicessuchastimeseries,images,andaudiowillbecovered.UsefulcasestudiesonfourmajorapplicationareasofIoTsolutionsareakeyfocalpointofthisbook.Intheconcludingchapters,youwillleveragethepowerofwidelyusedPythonlibraries,TensorFlowandKeras,tobuilddifferentkindsofsmartAImodels.Bytheendofthisbook,youwillbeabletobuildsmartAI-poweredIoTappswithconfidence.

·7.5萬字

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Hands-On Artificial Intelligence on Amazon Web Services

Fromdatawranglingthroughtotranslatingtext,youcanaccomplishthisandmorewiththeartificialintelligenceandmachinelearningservicesavailableonAWS.Withthisbook,you’llworkthroughhands-onexercisesandlearntousetheseservicestosolvereal-worldproblems.You’llevendesign,develop,monitor,andmaintainmachineanddeeplearningmodelsonAWS.ThebookstartswithanintroductiontoAIanditsapplicationsindifferentindustries,alongwithanoverviewofAWSartificialintelligenceandmachinelearningservices.You’llthengettogripswithdetectingandtranslatingtextwithAmazonRekognitionandAmazonTranslate.Thebookwillassistyouinperformingspeech-to-textwithAmazonTranscribeandAmazonPolly.Later,you’lldiscovertheuseofAmazonComprehendforextractinginformationfromtext,andAmazonLexforbuildingvoicechatbots.YouwillalsounderstandthekeycapabilitiesofAmazonSageMakersuchaswranglingbigdata,discoveringtopicsintextcollections,andclassifyingimages.Finally,you’llcoversalesforecastingwithdeeplearningandautoregression,beforeexploringtheimportanceofafeedbackloopinmachinelearning.Bytheendofthisbook,youwillhavetheskillsyouneedtoimplementAIinAWSthroughhands-onexercisesthatcoverallaspectsoftheMLmodellifecycle.

·8.2萬字

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Mastering Docker Enterprise

Whileknownmostlyastheopensourceenginebehindtensofmillionsofservernodes,DockeralsoofferscommerciallysupportedenterprisetoolingknownastheDockerEnterprise.ThisplatformleveragesthedeeprootsfromDockerEngine-Community(formerlyDockerCE)andKubernetes,butaddssupportandtoolingtoefficientlyoperateasecurecontainerplatformatscale.Withhundredsofenterprisesonboard,bestpracticesandadoptionpatternsareemergingrapidly.Theselearningpointscanbeusedtoinformadoptersandhelpmanagetheenterprisetransformationassociatedwithenterprisecontaineradoption.ThisbookstartsbyexplainingthecaseforDockerEnterprise,aswellasitsstructureandreferencearchitecture.Fromthere,weprogressthroughthePoC,pilotandproductionstagesasaworkingmodelforadoption,evolvingtheplatform’sdesignandconfigurationforeachstageandusingdetailedapplicationexamplesalongthewaytoclarifyanddemonstrateimportantconcepts.ThebookconcludeswithDocker’simpactonotheremergingsoftwaretechnologies,suchasBlockchainandServerlesscomputing.Bytheendofthisbook,you’llhaveabetterunderstandingofwhatittakestogetyourenterpriseupandrunningwithDockerEnterpriseandbeyond.

·10.9萬字

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R Graph Essentials

ThisbookistargetedatRprogrammerswhowanttolearnthegraphingcapabilitiesofR.ThisbookwillpresumethatyouhaveworkingknowledgeofR.

·2.4萬字

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Machine Learning with Apache Spark Quick Start Guide

Everypersonandeveryorganizationintheworldmanagesdata,whethertheyrealizeitornot.Dataisusedtodescribetheworldaroundusandcanbeusedforalmostanypurpose,fromanalyzingconsumerhabitstofightingdiseaseandseriousorganizedcrime.Ultimately,wemanagedatainordertoderivevaluefromit,andmanyorganizationsaroundtheworldhavetraditionallyinvestedintechnologytohelpprocesstheirdatafasterandmoreefficiently.Butwenowliveinaninterconnectedworlddrivenbymassdatacreationandconsumptionwheredataisnolongerrowsandcolumnsrestrictedtoaspreadsheet,butanorganicandevolvingassetinitsownright.Withthisrealizationcomesmajorchallengesfororganizations:howdowemanagethesheersizeofdatabeingcreatedeverysecond(thinknotonlyspreadsheetsanddatabases,butalsosocialmediaposts,images,videos,music,blogsandsoon)?Andoncewecanmanageallofthisdata,howdowederiverealvaluefromit?ThefocusofMachineLearningwithApacheSparkistohelpusanswerthesequestionsinahands-onmanner.Weintroducethelatestscalabletechnologiestohelpusmanageandprocessbigdata.Wethenintroduceadvancedanalyticalalgorithmsappliedtoreal-worldusecasesinordertouncoverpatterns,deriveactionableinsights,andlearnfromthisbigdata.

·5.2萬字

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Hands-On Predictive Analytics with Python

Predictiveanalyticsisanappliedfieldthatemploysavarietyofquantitativemethodsusingdatatomakepredictions.Itinvolvesmuchmorethanjustthrowingdataontoacomputertobuildamodel.Thisbookprovidespracticalcoveragetohelpyouunderstandthemostimportantconceptsofpredictiveanalytics.Usingpractical,step-by-stepexamples,webuildpredictiveanalyticssolutionswhileusingcutting-edgePythontoolsandpackages.Thebook'sstep-by-stepapproachstartsbydefiningtheproblemandmovesontoidentifyingrelevantdata.Wewillalsobeperformingdatapreparation,exploringandvisualizingrelationships,buildingmodels,tuning,evaluating,anddeployingmodel.EachstagehasrelevantpracticalexamplesandefficientPythoncode.YouwillworkwithmodelssuchasKNN,RandomForests,andneuralnetworksusingthemostimportantlibrariesinPython'sdatasciencestack:NumPy,Pandas,Matplotlib,Seaborn,Keras,Dash,andsoon.Inadditiontohands-oncodeexamples,youwillfindintuitiveexplanationsoftheinnerworkingsofthemaintechniquesandalgorithmsusedinpredictiveanalytics.Bytheendofthisbook,youwillbeallsettobuildhigh-performancepredictiveanalyticssolutionsusingPythonprogramming.

·7.1萬字

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Kibana 7 Quick Start Guide

TheElasticStackisgrowingrapidlyand,daybyday,additionaltoolsarebeingaddedtomakeitmoreeffective.ThisbookendeavorstoexplainalltheimportantaspectsofKibana,whichisessentialforutilizingitsfullpotential.ThisbookcoversthecoreconceptsofKibana,withchapterssetoutinacoherentmannersothatreaderscanadvancetheirlearninginastep-by-stepmanner.Thefocusisonapracticalapproach,therebyenablingthereadertoapplythoseexamplesinrealtimeforabetterunderstandingoftheconceptsandtoprovidethemwiththecorrectskillsinrelationtothetool.Withitssuccinctexplanations,itisquiteeasyforareadertousethisbookasareferenceguideforlearningbasictoadvancedimplementationsofKibana.Thepracticalexamples,suchasthecreationofKibanadashboardsfromCSVdata,applicationRDBMSdata,systemmetricsdata,logfiledata,APMagents,andsearchresults,canprovidereaderswithanumberofdifferentdrop-offpointsfromwheretheycanfetchanytypeofdataintoKibanaforthepurposeofanalysisordashboarding.

·3.2萬字

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Machine Learning with R

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.

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Microsoft System Center Confi guration Manager

Thisbookisastep-by-steptutorialthatguidesyouthroughthekeystepsinimplementingbestsolutionsforhighavailabilityandperformancetuning.Itissplitintotwodistinctapproaches:clientandsitesideHAandoptimization.MicrosoftSCCMHighAvailabilityandPerformanceTuningisforITprofessionalsandconsultantsworkingwithConfigurationManagerwhowishtolearntheskillstodeployaredundantandscalablesolution.

·2.8萬字

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Healthcare Analytics Made Simple

Inrecentyears,machinelearningtechnologiesandanalyticshavebeenwidelyutilizedacrossthehealthcaresector.HealthcareAnalyticsMadeSimplebridgesthegapbetweenpractisingdoctorsanddatascientists.Itequipsthedatascientists’workwithhealthcaredataandallowsthemtogainbetterinsightfromthisdatainordertoimprovehealthcareoutcomes.Thisbookisacompleteoverviewofmachinelearningforhealthcareanalytics,brieflydescribingthecurrenthealthcarelandscape,machinelearningalgorithms,andPythonandSQLprogramminglanguages.Thestep-by-stepinstructionsteachyouhowtoobtainrealhealthcaredataandperformdescriptive,predictive,andprescriptiveanalyticsusingpopularPythonpackagessuchaspandasandscikit-learn.Thelatestresearchresultsindiseasedetectionandhealthcareimageanalysisarereviewed.Bytheendofthisbook,youwillunderstandhowtousePythonforhealthcaredataanalysis,howtoimport,collect,clean,andrefinedatafromelectronichealthrecord(EHR)surveys,andhowtomakepredictivemodelswiththisdatathroughreal-worldalgorithmsandcodeexamples.

·6.3萬字

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Visualforce Development Cookbook（Second Edition）

Thisbookwillbebeneficialtodeveloperswhoarealreadywell-versedwiththebasicsofVisualforce.Anawarenessofthestandardcomponentlibraryandthepurposeofcontrollersisexpected.

·6.2萬字

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Machine Learning with Scala Quick Start Guide

Scalaisahighlyscalableintegrationofobject-orientednatureandfunctionalprogrammingconceptsthatmakeiteasytobuildscalableandcomplexbigdataapplications.ThisbookisahandyguideformachinelearningdevelopersanddatascientistswhowanttodevelopandtraineffectivemachinelearningmodelsinScala.Thebookstartswithanintroductiontomachinelearning,whilecoveringdeeplearningandmachinelearningbasics.ItthenexplainshowtouseScala-basedMLlibrariestosolveclassificationandregressionproblemsusinglinearregression,generalizedlinearregression,logisticregression,supportvectormachine,andNa?veBayesalgorithms.Italsocoverstree-basedensembletechniquesforsolvingbothclassificationandregressionproblems.Movingahead,itcoversunsupervisedlearningtechniques,suchasdimensionalityreduction,clustering,andrecommendersystems.Finally,itprovidesabriefoverviewofdeeplearningusingareal-lifeexampleinScala.

·4.5萬字

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Mastering Text Mining with R

Mastertext-tamingtechniquesandbuildeffectivetext-processingapplicationswithRAboutThisBook?Developalltherelevantskillsforbuildingtext-miningappswithRwiththiseasy-to-followguide?Gainin-depthunderstandingofthetextminingprocesswithlucidimplementationintheRlanguage?Example-richguidethatletsyougainhigh-qualityinformationfromtextdataWhoThisBookIsForIfyouareanRprogrammer,analyst,ordatascientistwhowantstogainexperienceinperformingtextdataminingandanalyticswithR,thenthisbookisforyou.Exposuretoworkingwithstatisticalmethodsandlanguageprocessingwouldbehelpful.WhatYouWillLearn?GetacquaintedwithsomeofthehighlyefficientRpackagessuchasOpenNLPandRWekatoperformvariousstepsinthetextminingprocess?AccessandmanipulatedatafromdifferentsourcessuchasJSONandHTTP?Processtextusingregularexpressions?Gettoknowthedifferentapproachesoftaggingtexts,suchasPOStagging,togetstartedwithtextanalysis?Exploredifferentdimensionalityreductiontechniques,suchasPrincipalComponentAnalysis(PCA),andunderstanditsimplementationinR?Discovertheunderlyingthemesortopicsthatarepresentinanunstructuredcollectionofdocuments,usingcommontopicmodelssuchasLatentDirichletAllocation(LDA)?Buildabaselinesentencecompletingapplication?PerformentityextractionandnamedentityrecognitionusingRInDetailTextMining(ortextdataminingortextanalytics)istheprocessofextractingusefulandhigh-qualityinformationfromtextbydevisingpatternsandtrends.Rprovidesanextensiveecosystemtominetextthroughitsmanyframeworksandpackages.Startingwithbasicinformationaboutthestatisticsconceptsusedintextmining,thisbookwillteachyouhowtoaccess,cleanse,andprocesstextusingtheRlanguageandwillequipyouwiththetoolsandtheassociatedknowledgeaboutdifferenttagging,chunking,andentailmentapproachesandtheirusageinnaturallanguageprocessing.Movingon,thisbookwillteachyoudifferentdimensionalityreductiontechniquesandtheirimplementationinR.Next,wewillcoverpatternrecognitionintextdatautilizingclassificationmechanisms,performentityrecognition,anddevelopanontologylearningframework.Bytheendofthebook,youwilldevelopapracticalapplicationfromtheconceptslearned,andwillunderstandhowtextminingcanbeleveragedtoanalyzethemassivelyavailabledataonsocialmedia.StyleandapproachThisbooktakesahands-on,example-drivenapproachtothetextminingprocesswithlucidimplementationinR.