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Managingphysicalserverswillbeathingofthepastonceyou’reabletoharnessthepowerofserverlesscomputing.Ifyou’realreadypreppedwiththebasicsofserverlesscomputing,ServerlessProgrammingCookbookwillhelpyoutakethenextstepahead.Thisrecipe-basedguideprovidessolutionstoproblemsyoumightfacewhilebuildingserverlessapplications.You'llbeginbysettingupAmazonWebServices(AWS),theprimarycloudproviderusedformostrecipes.ThenextsetofrecipeswillcovervariouscomponentstobuildaServerlessapplicationincludingRESTAPIs,database,usermanagement,authentication,webhosting,domainregistration,DNSmanagement,CDN,messaging,notificationsandmonitoring.ThebookalsointroducesyoutothelatesttechnologytrendssuchasDataStreams,MachineLearningandNLP.Youwillalsoseepatternsandpracticesforusingvariousservicesinarealworldapplication.Finally,tobroadenyourunderstandingofServerlesscomputing,you'llalsocovergettingstartedguidesforothercloudproviderssuchasAzure,GoogleCloudPlatformandIBMcloud.Bytheendofthisbook,you’llhaveacquiredtheskillsyouneedtobuildserverlessapplicationsefficientlyusingvariouscloudofferings.

·8.1萬字

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Generative Adversarial Networks Projects

GenerativeAdversarialNetworks(GANs)havethepotentialtobuildnext-generationmodels,astheycanmimicanydistributionofdata.Majorresearchanddevelopmentworkisbeingundertakeninthisfieldsinceitisoneoftherapidlygrowingareasofmachinelearning.Thisbookwilltestunsupervisedtechniquesfortrainingneuralnetworksasyoubuildsevenend-to-endprojectsintheGANdomain.GenerativeAdversarialNetworkProjectsbeginsbycoveringtheconcepts,tools,andlibrariesthatyouwillusetobuildefficientprojects.Youwillalsouseavarietyofdatasetsforthedifferentprojectscoveredinthebook.Thelevelofcomplexityoftheoperationsrequiredincreaseswitheverychapter,helpingyougettogripswithusingGANs.Youwillcoverpopularapproachessuchas3D-GAN,DCGAN,StackGAN,andCycleGAN,andyou’llgainanunderstandingofthearchitectureandfunctioningofgenerativemodelsthroughtheirpracticalimplementation.Bytheendofthisbook,youwillbereadytobuild,train,andoptimizeyourownend-to-endGANmodelsatworkorinyourownprojects.

·5.2萬字

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Ensemble Machine Learning Cookbook

Ensemblemodelingisanapproachusedtoimprovetheperformanceofmachinelearningmodels.Itcombinestwoormoresimilarordissimilarmachinelearningalgorithmstodeliversuperiorintellectualpowers.Thisbookwillhelpyoutoimplementpopularmachinelearningalgorithmstocoverdifferentparadigmsofensemblemachinelearningsuchasboosting,bagging,andstacking.TheEnsembleMachineLearningCookbookwillstartbygettingyouacquaintedwiththebasicsofensembletechniquesandexploratorydataanalysis.You'llthenlearntoimplementtasksrelatedtostatisticalandmachinelearningalgorithmstounderstandtheensembleofmultipleheterogeneousalgorithms.Itwillalsoensurethatyoudon'tmissoutonkeytopics,suchaslikeresamplingmethods.Asyouprogress,you’llgetabetterunderstandingofbagging,boosting,stacking,andworkingwiththeRandomForestalgorithmusingreal-worldexamples.Thebookwillhighlighthowtheseensemblemethodsusemultiplemodelstoimprovemachinelearningresults,ascomparedtoasinglemodel.Intheconcludingchapters,you'lldelveintoadvancedensemblemodelsusingneuralnetworks,naturallanguageprocessing,andmore.You’llalsobeabletoimplementmodelssuchasfrauddetection,textcategorization,andsentimentanalysis.Bytheendofthisbook,you'llbeabletoharnessensembletechniquesandtheworkingmechanismsofmachinelearningalgorithmstobuildintelligentmodelsusingindividualrecipes.

·5.5萬字

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Ceph：Designing and Implementing Scalable Storage Systems

ThisLearningPathtakesyouthroughthebasicsofCephallthewaytogainingin-depthunderstandingofitsadvancedfeatures.You’llgatherskillstoplan,deploy,andmanageyourCephcluster.AfteranintroductiontotheCepharchitectureanditscoreprojects,you’llbeabletosetupaCephclusterandlearnhowtomonitoritshealth,improveitsperformance,andtroubleshootanyissues.Byfollowingthestep-by-stepapproachofthisLearningPath,you’lllearnhowCephintegrateswithOpenStack,Glance,Manila,Swift,andCinder.WithknowledgeoffederatedarchitectureandCephFS,you’lluseCalamariandVSMtomonitortheCephenvironment.Intheupcomingchapters,you’llstudythekeyareasofCeph,includingBlueStore,erasurecoding,andcachetiering.Morespecifically,you’lldiscoverwhattheycandoforyourstoragesystem.Intheconcludingchapters,youwilldevelopapplicationsthatuseLibradosanddistributedcomputationswithsharedobjectclasses,andseehowCephanditssupportinginfrastructurecanbeoptimized.BytheendofthisLearningPath,you'llhavethepracticalknowledgeofoperatingCephinaproductionenvironment.ThisLearningPathincludescontentfromthefollowingPacktproducts:CephCookbookbyMichaelHackett,VikhyatUmraoandKaranSingh.MasteringCephbyNickFisk.LearningCeph,SecondEditionbyAnthonyD'Atri,VaibhavBhembreandKaranSingh.

·10.8萬字

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Mastering Hadoop 3

ApacheHadoopisoneofthemostpopularbigdatasolutionsfordistributedstorageandforprocessinglargechunksofdata.WithHadoop3,Apachepromisestoprovideahigh-performance,morefault-tolerant,andhighlyefficientbigdataprocessingplatform,withafocusonimprovedscalabilityandincreasedefficiency.Withthisguide,you’llunderstandadvancedconceptsoftheHadoopecosystemtool.You’lllearnhowHadoopworksinternally,studyadvancedconceptsofdifferentecosystemtools,discoversolutionstoreal-worldusecases,andunderstandhowtosecureyourcluster.ItwillthenwalkyouthroughHDFS,YARN,MapReduce,andHadoop3concepts.You’llbeabletoaddresscommonchallengeslikeusingKafkaefficiently,designinglowlatency,reliablemessagedeliveryKafkasystems,andhandlinghighdatavolumes.Asyouadvance,you’lldiscoverhowtoaddressmajorchallengeswhenbuildinganenterprise-grademessagingsystem,andhowtousedifferentstreamprocessingsystemsalongwithKafkatofulfilyourenterprisegoals.Bytheendofthisbook,you’llhaveacompleteunderstandingofhowcomponentsintheHadoopecosystemareeffectivelyintegratedtoimplementafastandreliabledatapipeline,andyou’llbeequippedtotacklearangeofreal-worldproblemsindatapipelines.

·12.1萬字

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Hands-On Business Intelligence with Qlik Sense

QlikSenseallowsyoutoexploresimple-to-complexdatatorevealhiddeninsightsanddatarelationshipstomakebusiness-drivendecisions.Hands-OnBusinessIntelligencewithQlikSensebeginsbyhelpingyougettogripswithunderlyingQlikconceptsandgivesyouanoverviewofallQlikSense’sfeatures.Youwilllearnadvancedmodelingtechniquesandlearnhowtoanalyzethedataloadedusingavarietyofvisualizationobjects.You’llalsobetrainedonhowtoshareappsthroughQlikSenseEnterpriseandQlikSenseCloudandhowtoperformaggregationwithAGGR.Asyouprogressthroughthechapters,you’llexplorethestoriesfeaturetocreatedata-drivenpresentationsandupdateanexistingstory.ThisbookwillguideyouthroughtheGeoAnalyticsfeaturewiththegeo-mappingobjectandGeoAnalyticsconnector.Furthermore,you’lllearnabouttheself-serviceanalyticsfeaturesandperformdataforecastingusingadvancedanalytics.Lastly,you’lldeployQlikSenseappsformobileandtablet.Bytheendofthisbook,youwillbewell-equippedtorunsuccessfulbusinessintelligenceapplicationsusingQlikSense'sfunctionality,datamodelingtechniques,andvisualizationbestpractices.

·5.4萬字

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Installation，Storage，and Compute with Windows Server 2016：Microsoft 70-740 MCSA Exam Guide

MCSA:WindowsServer2016certificationisoneofthemostsought-aftercertificationsforITprofessionals,whichincludesworkingwithWindowsServerandperformingadministrativetasksaroundit.Thisbookisaimedatthe70-740certificationandispartofPackt'sthree-bookseriesonMCSAWindowsServer2016certification,whichcoversExam70-740,Exam70-741,andExam70-742.Thisbookwillcoverexamobjectivesforthe70-740exam,andstartingfrominstallingandconfiguringWindowsServer2016,WindowsServerimaginganddeploymenttoconfiguringandmanagingdisksandvolumes,implementingandconfiguringserverstorageandimplementingHyper-V.Attheendofeachchapteryouwillbeprovidedtestquestionstoreviseyourlearningswhichwillboostyourconfidenceinpreparingfortheactualcertifications.Bytheendofthisbook,youwilllearneverythingneededtopassthe,MCSAExam70-740:Installation,Storage,andComputewithWindowsServer2016,certification.

·5.2萬字

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Python Machine Learning By Example

Thesurgeininterestinmachinelearning(ML)isduetothefactthatitrevolutionizesautomationbylearningpatternsindataandusingthemtomakepredictionsanddecisions.Ifyou’reinterestedinML,thisbookwillserveasyourentrypointtoML.PythonMachineLearningByExamplebeginswithanintroductiontoimportantMLconceptsandimplementationsusingPythonlibraries.Eachchapterofthebookwalksyouthroughanindustryadoptedapplication.You’llimplementMLtechniquesinareassuchasexploratorydataanalysis,featureengineering,andnaturallanguageprocessing(NLP)inaclearandeasy-to-followway.Withthehelpofthisextendedandupdatededition,you’llunderstandhowtotackledata-drivenproblemsandimplementyoursolutionswiththepowerfulyetsimplePythonlanguageandpopularPythonpackagesandtoolssuchasTensorFlow,scikit-learn,gensim,andKeras.ToaidyourunderstandingofpopularMLalgorithms,thebookcoversinterestingandeasy-to-followexamplessuchasnewstopicmodelingandclassification,spamemaildetection,stockpriceforecasting,andmore.Bytheendofthebook,you’llhaveputtogetherabroadpictureoftheMLecosystemandwillbewell-versedwiththebestpracticesofapplyingMLtechniquestomakethemostoutofnewopportunities.

·7.7萬字

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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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Building Google Cloud Platform Solutions

GCPisacloudcomputingplatformwithawiderangeofproductsandservicesthatenableyoutobuildanddeploycloud-hostedapplications.ThisLearningPathwillguideyouinusingGCPanddesigning,deploying,andmanagingapplicationsonGoogleCloud.YouwillgetstartedbylearninghowtouseAppEnginetoaccessGoogle'sscalablehostingandbuildsoftwarethatrunsonthisframework.WiththehelpofGoogleComputeEngine,you’llbeabletohostyourworkloadonvirtualmachineinstances.Thelaterchapterswillhelpyoutoexplorewaystoimplementauthenticationandsecurity,CloudAPIs,andcommand-lineanddeploymentmanagement.Asyouhoneyourskills,you’llunderstandhowtointegrateyournewapplicationswithvariousdatasolutionsonGCP,includingCloudSQL,Bigtable,andCloudStorage.Followingthis,thebookwillteachyouhowtostreamlineyourworkflowwithtools,includingSourceRepositories,ContainerBuilder,andStackdriver.You'llalsounderstandhowtodeployanddebugserviceswithIntelliJ,implementcontinuousdeliverypipelines,andconfigurerobustmonitoringandalertsforyourproductionsystems.BytheendofthisLearningPath,you'llbewellversedwithGCP’sdevelopmenttoolsandbeabletodevelop,deploy,andmanagehighlyscalableandreliableapplications.ThisLearningPathincludescontentfromthefollowingPacktproducts:GoogleCloudPlatformforDevelopersTedHunterandStevenPorter.GoogleCloudPlatformCookbookbyLegorieRajanPS.

·16.2萬字

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Getting Started with Containerization

Kubernetesisanopensourceorchestrationplatformformanagingcontainersinaclusterenvironment.ThisLearningPathintroducesyoutotheworldofcontainerization,inadditiontoprovidingyouwithanoverviewofDockerfundamentals.Asyouprogress,youwillbeabletounderstandhowKubernetesworkswithcontainers.StartingwithcreatingKubernetesclustersandrunningapplicationswithproperauthenticationandauthorization,you'lllearnhowtocreatehigh-availabilityKubernetesclustersonAmazonWebServices(AWS),andalsolearnhowtousekubeconfigtomanagedifferentclusters.WhetheritislearningaboutDockercontainersandDockerCompose,orbuildingacontinuousdeliverypipelineforyourapplication,thisLearningPathwillequipyouwithalltherighttoolsandtechniquestogetstartedwithcontainerization.BytheendofthisLearningPath,youwillhavegainedhands-onexperienceofworkingwithDockercontainersandorchestrators,includingSwarmKitandKubernetes.ThisLearningPathincludescontentfromthefollowingPacktproducts:KubernetesCookbook-SecondEditionbyHidetoSaito,Hui-ChuanChloeLee,andKe-JouCarolHsu.LearnDocker-FundamentalsofDocker18.xbyGabrielN.Schenker.

·13.9萬字

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Learning Python Networking（Second Edition）

Networkprogramminghasalwaysbeenademandingtask.Withfull-featuredandwell-documentedlibrariesallthewayupthestack,Pythonmakesnetworkprogrammingtheenjoyableexperienceitshouldbe.Startingwithawalkthroughoftoday'smajornetworkingprotocols,throughthisbook,you'lllearnhowtoemployPythonfornetworkprogramming,howtorequestandretrievewebresources,andhowtoextractdatainmajorformatsovertheweb.YouwillutilizePythonforemailingusingdifferentprotocols,andyou'llinteractwithremotesystemsandIPandDNSnetworking.YouwillcovertheconnectionofnetworkingdevicesandconfigurationusingPython3.7,alongwithcloud-basednetworkmanagementtasksusingPython.Asthebookprogresses,socketprogrammingwillbecovered,followedbyhowtodesignservers,andtheprosandconsofmultithreadedandevent-drivenarchitectures.You'lldeveloppracticalclientsideapplications,includingwebAPIclients,emailclients,SSH,andFTP.Theseapplicationswillalsobeimplementedthroughexistingwebapplicationframeworks.

·9.6萬字

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Hands-On Neural Networks with Keras

NeuralnetworksareusedtosolveawiderangeofproblemsindifferentareasofAIanddeeplearning.Hands-OnNeuralNetworkswithKeraswillstartwithteachingyouaboutthecoreconceptsofneuralnetworks.Youwilldelveintocombiningdifferentneuralnetworkmodelsandworkwithreal-worldusecases,includingcomputervision,naturallanguageunderstanding,syntheticdatageneration,andmanymore.Movingon,youwillbecomewellversedwithconvolutionalneuralnetworks(CNNs),recurrentneuralnetworks(RNNs),longshort-termmemory(LSTM)networks,autoencoders,andgenerativeadversarialnetworks(GANs)usingreal-worldtrainingdatasets.WewillexaminehowtouseCNNsforimagerecognition,howtousereinforcementlearningagents,andmanymore.Wewilldiveintothespecificarchitecturesofvariousnetworksandthenimplementeachoftheminahands-onmannerusingindustry-gradeframeworks.Bytheendofthisbook,youwillbehighlyfamiliarwithallprominentdeeplearningmodelsandframeworks,andtheoptionsyouhavewhenapplyingdeeplearningtoreal-worldscenariosandembeddingartificialintelligenceasthecorefabricofyourorganization.

·11.4萬字

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Big Data Analysis with Python

Processingbigdatainrealtimeischallengingduetoscalability,informationinconsistency,andfaulttolerance.BigDataAnalysiswithPythonteachesyouhowtousetoolsthatcancontrolthisdataavalancheforyou.Withthisbook,you'lllearnpracticaltechniquestoaggregatedataintousefuldimensionsforposterioranalysis,extractstatisticalmeasurements,andtransformdatasetsintofeaturesforothersystems.ThebookbeginswithanintroductiontodatamanipulationinPythonusingpandas.You'llthengetfamiliarwithstatisticalanalysisandplottingtechniques.Withmultiplehands-onactivitiesinstore,you'llbeabletoanalyzedatathatisdistributedonseveralcomputersbyusingDask.Asyouprogress,you'llstudyhowtoaggregatedataforplotswhentheentiredatacannotbeaccommodatedinmemory.You'llalsoexploreHadoop(HDFSandYARN),whichwillhelpyoutacklelargerdatasets.ThebookalsocoversSparkandexplainshowitinteractswithothertools.Bytheendofthisbook,you'llbeabletobootstrapyourownPythonenvironment,processlargefiles,andmanipulatedatatogeneratestatistics,metrics,andgraphs.

·4萬字

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Python Data Mining Quick Start Guide

Dataminingisanecessaryandpredictableresponsetothedawnoftheinformationage.Itistypicallydefinedasthepatternand/ortrenddiscoveryphaseinthedataminingpipeline,andPythonisapopulartoolforperformingthesetasksasitoffersawidevarietyoftoolsfordatamining.ThisbookwillserveasaquickintroductiontotheconceptofdataminingandputtingittopracticalusewiththehelpofpopularPythonpackagesandlibraries.Youwillgetahands-ondemonstrationofworkingwithdifferentreal-worlddatasetsandextractingusefulinsightsfromthemusingpopularPythonlibrariessuchasNumPy,pandas,scikit-learn,andmatplotlib.Youwillthenlearnthedifferentstagesofdataminingsuchasdataloading,cleaning,analysis,andvisualization.Youwillalsogetafullconceptualdescriptionofpopulardatatransformation,clustering,andclassificationtechniques.Bytheendofthisbook,youwillbeabletobuildanefficientdataminingpipelineusingPythonwithoutanyhassle.

·3.5萬字

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Network Science with Python and NetworkX Quick Start Guide

NetworkXisaleadingfreeandopensourcepackageusedfornetworksciencewiththePythonprogramminglanguage.NetworkXcantrackpropertiesofindividualsandrelationships,findcommunities,analyzeresilience,detectkeynetworklocations,andperformawiderangeofimportanttasks.Withtherecentreleaseofversion2,NetworkXhasbeenupdatedtobemorepowerfulandeasytouse.Ifyou’readatascientist,engineer,orcomputationalsocialscientist,thisbookwillguideyouinusingthePythonprogramminglanguagetogaininsightsintoreal-worldnetworks.Startingwiththefundamentals,you’llbeintroducedtothecoreconceptsofnetworkscience,alongwithexamplesthatusereal-worlddataandPythoncode.Thisbookwillintroduceyoutotheoreticalconceptssuchasscale-freeandsmall-worldnetworks,centralitymeasures,andagent-basedmodeling.You’llalsobeabletolookforscale-freenetworksinrealdataandvisualizeanetworkusingcircular,directed,andshelllayouts.Bytheendofthisbook,you’llbeabletochooseappropriatenetworkrepresentations,useNetworkXtobuildandcharacterizenetworks,anduncoverinsightswhileworkingwithreal-worldsystems.

·3.7萬字

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Hands-On Linux for Architects

Itisveryimportanttounderstandtheflexibilityofaninfrastructurewhendesigninganefficientenvironment.Inthisbook,youwillcovereverythingfromLinuxcomponentsandfunctionalitiesthroughtohardwareandsoftwaresupport,whichwillhelpyoutoimplementandtuneeffectiveLinux-basedsolutions.ThisbookgetsstartedwithanoverviewofLinuxdesignmethodology.Next,youwillfocusonthecoreconceptsofdesigningasolution.Asyouprogress,youwillgaininsightsintothekindsofdecisionsyouneedtomakewhendeployingahigh-performancesolutionusingGlusterFileSystem(GlusterFS).Inthenextsetofchapters,thebookwillguideyouthroughthetechniqueofusingKubernetesasanorchestratorfordeployingandmanagingcontainerizedapplications.Inadditiontothis,youwilllearnhowtoapplyandconfigureKubernetesforyourNGINXapplication.You’llthenlearnhowtoimplementanELKstack,whichiscomposedofElasticsearch,Logstash,andKibana.Intheconcludingchapters,youwillfocusoninstallingandconfiguringaSaltstacksolutiontomanagedifferentLinuxdistributions,andexploreavarietyofdesignbestpractices.Bytheendofthisbook,youwillbewell-versedwithdesigningahigh-performingcomputingenvironmentforcomplexapplicationstorunon.Bytheendofthebook,youwillhavedelvedinsidethemostdetailedtechnicalconditionsofdesigningasolution,andyouwillhavealsodissectedeveryaspectindetailinordertoimplementandtuneopensourceLinux-basedsolutions.

·7.7萬字

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MCSA Windows Server 2016 Certification Guide：Exam 70-741

MCSA:WindowsServer2016isoneofthemostsought-aftercertificationsforITprofessionalswhichincludeworkingwithWindowsServerandperformingadministrativetasksaroundit.IttargetsExam70-740,Exam70-741,Exam70-742andExam70-743certificationsandthedemandforthesecertificationsisincreasinglyhigh.Thisbookwillstartwithinstallation,upgradeandmigrationtoWindowsServer2016,coverimaginganddeploymentandproceedwithHighAvailabilityandClustering.ThenwewilldeepdiveintofundamentalconceptslikeCorenetworking,DNS,DHCP,StorageandproceedtoHyper-V,NetworkAccessandDistributedFileSystem.ItwillalsoexplainAdvancedNetworkingtopicssuchasSoftwareDefinedNetworkingandHigh-PerformanceNetworking.Furthermore,itwillalsocoveradvancedIdentitytopicsinWindowsServer2016suchasActiveDirectoryinstallationandconfiguration,GroupPolicy,ActiveDirectoryCertificateServices,andActiveDirectoryFederationServicesandRightsManagement.Towardstheendofthisbook,testquestionsandmockpreparationitemswillhelpinpreparingforthecertificationswithmoreease.Bytheendofthisbook,youwillbeabletocompleteMCSA:WindowsServer2016certificationwithmoreconfidence.

·2.7萬字

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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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Hands-On Generative Adversarial Networks with Keras

GenerativeAdversarialNetworks(GANs)haverevolutionizedthefieldsofmachinelearninganddeeplearning.ThisbookwillbeyourfirststeptowardsunderstandingGANarchitecturesandtacklingthechallengesinvolvedintrainingthem.Thisbookopenswithanintroductiontodeeplearningandgenerativemodels,andtheirapplicationsinartificialintelligence(AI).Youwillthenlearnhowtobuild,evaluate,andimproveyourfirstGANwiththehelpofeasy-to-followexamples.ThenextfewchapterswillguideyouthroughtrainingaGANmodeltoproduceandimprovehigh-resolutionimages.YouwillalsolearnhowtoimplementconditionalGANsthatgiveyoutheabilitytocontrolcharacteristicsofGANoutputs.YouwillbuildonyourknowledgefurtherbyexploringanewtrainingmethodologyforprogressivegrowingofGANs.Movingon,you'llgaininsightsintostate-of-the-artmodelsinimagesynthesis,speechenhancement,andnaturallanguagegenerationusingGANs.Inadditiontothis,you'llbeabletoidentifyGANsampleswithTequilaGAN.Bytheendofthisbook,youwillbewell-versedwiththelatestadvancementsintheGANframeworkusingvariousexamplesanddatasets,andyouwillhavetheskillsyouneedtoimplementGANarchitecturesforseveraltasksanddomains,includingcomputervision,naturallanguageprocessing(NLP),andaudioprocessing.ForewordbyTing-ChunWang,SeniorResearchScientist,NVIDIA

·4.2萬字

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