怎么才能MG游戏爆分

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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Elasticsearch 7.0 Cookbook（Fourth Edition）

ElasticsearchisaLucene-baseddistributedsearchserverthatallowsuserstoindexandsearchunstructuredcontentwithpetabytesofdata.Withthisbook,you'llbeguidedthroughcomprehensiverecipesonwhat'snewinElasticsearch7,andseehowtocreateandruncomplexqueriesandanalytics.Packedwithrecipesonperformingindexmapping,aggregation,andscriptingusingElasticsearch,thisfourtheditionofElasticsearchCookbookwillgetyouacquaintedwithnumeroussolutionsandquicktechniquesforperformingbotheverydayanduncommontaskssuchasdeployingElasticsearchnodes,integratingothertoolstoElasticsearch,andcreatingdifferentvisualizations.YouwillinstallKibanatomonitoraclusterandalsoextenditusingavarietyofplugins.Finally,youwillintegrateyourJava,Scala,Python,andbigdataapplicationssuchasApacheSparkandPigwithElasticsearch,andcreateefficientdataapplicationspoweredbyenhancedfunctionalitiesandcustomplugins.Bytheendofthisbook,youwillhavegainedin-depthknowledgeofimplementingElasticsearcharchitecture,andyou'llbeabletomanage,search,andstoredataefficientlyandeffectivelyusingElasticsearch.

·12.8萬字

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Hands-On Deep Learning Architectures with Python

Deeplearningarchitecturesarecomposedofmultilevelnonlinearoperationsthatrepresenthigh-levelabstractions;thisallowsyoutolearnusefulfeaturerepresentationsfromthedata.Thisbookwillhelpyoulearnandimplementdeeplearningarchitecturestoresolvevariousdeeplearningresearchproblems.Hands-OnDeepLearningArchitectureswithPythonexplainstheessentiallearningalgorithmsusedfordeepandshallowarchitectures.Packedwithpracticalimplementationsandideastohelpyoubuildefficientartificialintelligencesystems(AI),thisbookwillhelpyoulearnhowneuralnetworksplayamajorroleinbuildingdeeparchitectures.Youwillunderstandvariousdeeplearningarchitectures(suchasAlexNet,VGGNet,GoogleNet)witheasy-to-followcodeanddiagrams.Inadditiontothis,thebookwillalsoguideyouinbuildingandtrainingvariousdeeparchitecturessuchastheBoltzmannmechanism,autoencoders,convolutionalneuralnetworks(CNNs),recurrentneuralnetworks(RNNs),naturallanguageprocessing(NLP),GAN,andmore—allwithpracticalimplementations.Bytheendofthisbook,youwillbeabletoconstructdeepmodelsusingpopularframeworksanddatasetswiththerequireddesignpatternsforeacharchitecture.Youwillbereadytoexplorethepotentialofdeeparchitecturesintoday'sworld.

·6.2萬字

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AWS Certified Advanced Networking：Specialty Exam Guide

Amazonhasrecentlycomeupawithspecialtycertificationswhichvalidatesaparticularuser'sexpertisethathe/shewouldwanttobuildacareerin.SincetheCloudmarketnowdemandsofAWSnetworkingskillsthisbecomesthemostwantedcertificationtoupheldonesindustryportfolio.Thisbookwouldbeyouridealcompaniontogettingskilledwithcomplexandcreativenetworkingsolutions.Cloudpractitionersorassociate-levelcertifiedindividualsinterestedinvalidatingadvancedskillsinnetworkingcanoptforthispracticalguide.ThisbookwillincludetopicsthatwillhelpyoudesignandimplementAWSandhybridITnetworkarchitecturesalongwithsomenetworkautomationtasks.YouwillalsodelvedeepintotopicsthatwillhelpyoudesignandmaintainnetworkarchitectureforallAWSservices.Likemostofourcertificationguidesthisbookwillalsofollowauniqueapproachoftestingyourlearningwithchapter-levelpracticeexercisesandcertification-basedmocktests.Theexammocktestswillhelpyougaugewhetheryouarereadytotakethecertificationexamornot.Thisbookwillalsobeanadvancedguidefornetworkingprofessionalstoenhancetheirnetworkingskillsandgetcertified.Bytheendofthisbook,youwillbeallequippedwithAWSnetworkingconceptsandtechniquesandwillhavemasteredcorearchitecturalbestpractices.

·6.4萬字

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Learning Elastic Stack 7.0（Second Edition）

TheElasticStackisapowerfulcombinationoftoolsfortechniquessuchasdistributedsearch,analytics,logging,andvisualizationofdata.ElasticStack7.0encompassesnewfeaturesandcapabilitiesthatwillenableyoutofinduniqueinsightsintoanalyticsusingthesetechniques.Thisbookwillgiveyouafundamentalunderstandingofwhatthestackisallabout,andhelpyouuseitefficientlytobuildpowerfulreal-timedataprocessingapplications.Thefirstfewsectionsofthebookwillhelpyouunderstandhowtosetupthestackbyinstallingtools,andexploringtheirbasicconfigurations.You’llthengetuptospeedwithusingElasticsearchfordistributedsearchingandanalytics,Logstashforlogging,andKibanafordatavisualization.Asyouworkthroughthebook,youwilldiscoverthetechniqueofcreatingcustompluginsusingKibanaandBeats.ThisisfollowedbycoverageoftheElasticX-Pack,ausefulextensionforeffectivesecurityandmonitoring.You’llalsofindhelpfultipsonhowtouseElasticCloudanddeployElasticStackinproductionenvironments.Bytheendofthisbook,you’llbewellversedwiththefundamentalElasticStackfunctionalitiesandtheroleofeachcomponentinthestacktosolvedifferentdataprocessingproblems.

·8.6萬字

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Hands-On Exploratory Data Analysis with R

Hands-OnExploratoryDataAnalysiswithRwillhelpyoubuildnotjustafoundationbutalsoexpertiseintheelementarywaystoanalyzedata.Youwilllearnhowtounderstandyourdataandsummarizeitsmaincharacteristics.You'llalsouncoverthestructureofyourdata,andyou'lllearngraphicalandnumericaltechniquesusingtheRlanguage.Thisbookcoverstheentireexploratorydataanalysis(EDA)process—datacollection,generatingstatistics,distribution,andinvalidatingthehypothesis.Asyouprogressthroughthebook,youwilllearnhowtosetupadataanalysisenvironmentwithtoolssuchasggplot2,knitr,andRMarkdown,usingtoolssuchasDOEScatterPlotandSML2010formultifactor,optimization,andregressiondataproblems.Bytheendofthisbook,youwillbeabletosuccessfullycarryoutapreliminaryinvestigationonanydataset,identifyhiddeninsights,andpresentyourresultsinabusinesscontext.

·3.6萬字

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Hands-On Neural Networks

Neuralnetworksplayaveryimportantroleindeeplearningandartificialintelligence(AI),withapplicationsinawidevarietyofdomains,rightfrommedicaldiagnosis,tofinancialforecasting,andevenmachinediagnostics.Hands-OnNeuralNetworksisdesignedtoguideyouthroughlearningaboutneuralnetworksinapracticalway.Thebookwillgetyoustartedbygivingyouabriefintroductiontoperceptronnetworks.YouwillthengaininsightsintomachinelearningandalsounderstandwhatthefutureofAIcouldlooklike.Next,youwillstudyhowembeddingscanbeusedtoprocesstextualdataandtheroleoflongshort-termmemorynetworks(LSTMs)inhelpingyousolvecommonnaturallanguageprocessing(NLP)problems.Thelaterchapterswilldemonstratehowyoucanimplementadvancedconceptsincludingtransferlearning,generativeadversarialnetworks(GANs),autoencoders,andreinforcementlearning.Finally,youcanlookforwardtofurthercontentonthelatestadvancementsinthefieldofneuralnetworks.Bytheendofthisbook,youwillhavetheskillsyouneedtobuild,train,andoptimizeyourownneuralnetworkmodelthatcanbeusedtoprovidepredictablesolutions.

·4.9萬字

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Geospatial Data Science Quick Start Guide

Datascientists,whohaveaccesstovastdatastreams,areabitmyopicwhenitcomestointrinsicandextrinsiclocation-baseddataandaremissingoutontheintelligenceitcanprovidetotheirmodels.Thisbookdemonstrateseffectivetechniquesforusingthepowerofdatascienceandgeospatialintelligencetobuildeffective,intelligentdatamodelsthatmakeuseoflocation-baseddatatogiveusefulpredictionsandanalyses.Thisbookbeginswithaquickoverviewofthefundamentalsoflocation-baseddataandhowtechniquessuchasExploratoryDataAnalysiscanbeappliedtoit.Wethendelveintospatialoperationssuchascomputingdistances,areas,extents,centroids,bufferpolygons,intersectinggeometries,geocoding,andmore,whichaddsadditionalcontexttolocationdata.Movingahead,youwilllearnhowtoquicklybuildanddeployageo-fencingsystemusingPython.Lastly,youwilllearnhowtoleveragegeospatialanalysistechniquesinpopularrecommendationsystemssuchascollaborativefilteringandlocation-basedrecommendations,andmore.Bytheendofthebook,youwillbearockstarwhenitcomestoperforminggeospatialanalysiswithease.

·3萬字

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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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Machine Learning for Cybersecurity Cookbook

Organizationstodayfaceamajorthreatintermsofcybersecurity,frommaliciousURLstocredentialreuse,andhavingrobustsecuritysystemscanmakeallthedifference.Withthisbook,you'lllearnhowtousePythonlibrariessuchasTensorFlowandscikit-learntoimplementthelatestartificialintelligence(AI)techniquesandhandlechallengesfacedbycybersecurityresearchers.You'llbeginbyexploringvariousmachinelearning(ML)techniquesandtipsforsettingupasecurelabenvironment.Next,you'llimplementkeyMLalgorithmssuchasclustering,gradientboosting,randomforest,andXGBoost.Thebookwillguideyouthroughconstructingclassifiersandfeaturesformalware,whichyou'lltrainandtestonrealsamples.Asyouprogress,you'llbuildself-learning,reliantsystemstohandlecybersecuritytaskssuchasidentifyingmaliciousURLs,spamemaildetection,intrusiondetection,networkprotection,andtrackinguserandprocessbehavior.Later,you'llapplygenerativeadversarialnetworks(GANs)andautoencoderstoadvancedsecuritytasks.Finally,you'lldelveintosecureandprivateAItoprotecttheprivacyrightsofconsumersusingyourMLmodels.Bytheendofthisbook,you'llhavetheskillsyouneedtotacklereal-worldproblemsfacedinthecybersecuritydomainusingarecipe-basedapproach.

·5.6萬字

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Microsoft 365 Mobility and Security：Exam Guide MS-101

ExamMS-101:Microsoft365MobilityandSecurityisapartoftheMicrosoft365Certified:EnterpriseAdministratorExpertcertificationpathdesignedtohelpusersvalidatetheirskillsinevaluating,planning,migrating,deploying,andmanagingMicrosoft365services.Thisbookwillhelpyouimplementmoderndeviceservices,applyMicrosoft365securityandthreatmanagement,andmanageMicrosoft365governanceandcompliance.Writteninasuccinctway,you’llexplorechapter-wiseself-assessmentquestions,examtips,andmockexamswithanswers.You’llstartbyimplementingmobiledevicemanagement(MDM)andhandlingdevicecompliance.You’lldelveintothreatdetectionandmanagement,learninghowtomanagesecurityreportsandconfigureMicrosoft365alerts.Later,you’lldiscoverdatalossprevention(DLP)toolstoprotectdataaswellastoolsforconfiguringauditlogsandpolicies.ThebookwillalsoguideyouthroughusingAzureInformationProtection(AIP)fordeployingclients,applyingpolicies,andconfiguringservicesanduserstoenhancedatasecurity.Finally,you’llcoverbestpracticesforconfiguringsettingsacrossyourtenanttoensurecomplianceandsecurity.Bytheendofthisbook,you’llhavelearnedtoworkwithMicrosoft365servicesandcoveredtheconceptsandtechniquesyouneedtoknowtopasstheMS-101exam.