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Network Science with Python and NetworkX Quick Start Guide
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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.

Edward L. Platt ·自動化 ·3.7萬字

Hands-On Linux for Architects
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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.

Denis Salamanca Esteban Flores ·自動化 ·7.7萬字

MCSA Windows Server 2016 Certification Guide：Exam 70-741
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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.

Sasha Kranjac Vladimir Stefanovic ·自動化 ·2.7萬字

Machine Learning with Scala Quick Start Guide
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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.

Md. Rezaul Karim ·自動化 ·4.5萬字

Hands-On Generative Adversarial Networks with Keras
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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

Rafael Valle ·自動化 ·4.2萬字

Elasticsearch 7.0 Cookbook（Fourth Edition）
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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.

Alberto Paro ·自動化 ·12.8萬字

Hands-On Deep Learning Architectures with Python
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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.

Yuxi (Hayden) Liu Saransh Mehta ·自動化 ·6.2萬字

AWS Certified Advanced Networking：Specialty Exam Guide
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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.

Marko Sluga ·自動化 ·6.4萬字

Learning Elastic Stack 7.0（Second Edition）
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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.

Pranav Shukla Sharath Kumar M N ·自動化 ·8.6萬字

Hands-On Exploratory Data Analysis with R
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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.

Radhika Datar Harish Garg ·自動化 ·3.6萬字

Hands-On Neural Networks
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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.

Leonardo De Marchi Laura Mitchell ·自動化 ·4.9萬字

Geospatial Data Science Quick Start Guide
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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.

Abdishakur Hassan Jayakrishnan Vijayaraghavan ·自動化 ·3萬字

Hands-On Artificial Intelligence on Amazon Web Services
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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.

Subhashini Tripuraneni Charles Song ·自動化 ·8.2萬字

Machine Learning for Cybersecurity Cookbook
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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.

Emmanuel Tsukerman ·自動化 ·5.6萬字

Microsoft 365 Mobility and Security：Exam Guide MS-101
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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.

Nate Chamberlain ·自動化 ·4萬字

Learn SOLIDWORKS 2020
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Learn SOLIDWORKS 2020

SOLIDWORKSistheleadingchoicefor3Dengineeringandproductdesignapplicationsacrossindustriessuchasaviation,automobiles,andconsumerproductdesign.ThisbooktakesapracticalapproachtogettingyouupandrunningwithSOLIDWORKS2020.You'llstartwiththebasics,exploringthesoftwareinterfaceandworkingwithdrawingfiles.Thebookthenguidesyouthroughtopicssuchassketching,buildingcomplex3Dmodels,generatingdynamicandstaticassemblies,andgenerating2Dengineeringdrawingstoequipyouformechanicaldesignprojects.You'llalsodopracticalexercisestogethands-onwithcreatingsketches,3Dpartmodels,assemblies,anddrawings.ToreinforceyourunderstandingofSOLIDWORKS,thebookissupplementedbydownloadablefilesthatwillhelpyoufollowupwiththeconceptsandexercisesfoundinthebook.Bytheendofthisbook,you'llhavegainedtheskillsyouneedtocreateprofessional3DmechanicalmodelsusingSOLIDWORKS,andyou'llbeabletoprepareeffectivelyfortheCertifiedSOLIDWORKSAssociate(CSWA)andCertifiedSOLIDWORKSProfessional(CSWP)exams.

Tayseer Almattar ·自動化 ·7.6萬字

Hands-On Edge Analytics with Azure IoT
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Hands-On Edge Analytics with Azure IoT

EdgeanalyticshasgainedattentionastheIoTmodelforconnecteddevicesrisesinpopularity.Thisguidewillgiveyouinsightsintoedgeanalyticsasadataanalysismodel,andhelpyouunderstandwhyit’sgainingmomentum.You'llbeginwiththekeyconceptsandcomponentsusedinanedgeanalyticsapp.Movingahead,you'lldelveintocommunicationprotocolstounderstandhowsensorssendtheirdatatocomputersormicrocontrollers.Next,thebookwilldemonstratehowtodesignmodernedgeanalyticsappsthattakeadvantageoftheprocessingpowerofmodernsingle-boardcomputersandmicrocontrollers.Later,you'llexploreMicrosoftAzureIoTEdge,MicroPython,andtheOpenCVvisualrecognitionlibrary.Asyouprogress,you'llcovertechniquesforprocessingAIfunctionalitiesfromtheserversidetothesensorysideofIoT.You'llevengethands-onwithdesigningasmartdoorbellsystemusingthetechnologiesyou’velearned.Toremovevulnerabilitiesintheoveralledgeanalyticsarchitecture,you'lldiscoverwaystoovercomesecurityandprivacychallenges.Finally,you'llusetoolstoauditandperformreal-timemonitoringofincomingdataandgeneratealertsfortheinfrastructure.Bytheendofthisbook,you'llhavelearnedhowtouseedgeanalyticsprogrammingtechniquesandbeabletoimplementautomatedanalyticalcomputations.

Colin Dow ·自動化 ·4.3萬字

Salesforce for Beginners
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Salesforce for Beginners

Salesforceistheworld'sleadingCustomerRelationshipManagement(CRM)software,helpingbusinessesconnectwiththeirconstituentsandpartners.Thisbookwillgiveyouacomprehensiveintroductiontomanagingsales,marketing,customerrelationships,andoveralladministrationforyourorganization.You'lllearnhowtoconfigureanduseSalesforceformaximumefficiencyandreturnoninvestment.You'llstartbylearninghowtocreateactivities,manageleads,anddevelopyourprospectsandsalespipelineusingopportunitiesandaccounts,andthenunderstandhowyoucanenhancemarketingactivitiesusingcampaigns.Packedwithreal-worldbusinessusecases,thisSalesforcebookwillshowyouhowtoanalyzeyourbusinessinformationaccuratelytomakeproductivedecisions.Asyouadvance,you'llgettogripswithbuildingvariousreportsanddashboardsinSalesforcetoderivevaluablebusinessinsights.Finally,you'llexploretoolssuchasprocessbuilder,approvalprocesses,andassignmentrulestoachievebusinessprocessautomationandsetoutonthepathtobecomingasuccessfulSalesforceAdministrator.Bytheendofthebook,you'llhavelearnedhowtouseSalesforceeffectivelytoachieveyourbusinessgoals.

Sharif Shaalan ·自動化 ·5.7萬字

Learn Grafana 7.0
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Learn Grafana 7.0

Grafanaisanopen-sourceanalyticalplatformusedtoanalyzeandmonitoringtime-seriesdata.Thisbeginner'sguidewillhelpyougettogripswithGrafana'snewfeaturesforquerying,visualizing,andexploringmetricsandlogsnomatterwheretheyarestored.ThebookbeginsbyshowingyouhowtoinstallandsetuptheGrafanaserver.You'llexploretheworkingmechanismofvariouscomponentsoftheGrafanainterfacealongwithitssecurityfeatures,andlearnhowtovisualizeandmonitordatausing,InfluxDB,Prometheus,Logstash,andElasticsearch.ThisGrafanabookcoverstheadvancedfeaturesoftheGraphpanelandshowsyouhowStat,Table,BarGauge,andTextareused.You'llbuilddynamicdashboardstoperformend-to-endanalyticsandlabelandorganizedashboardsintofolderstomakethemeasiertofind.Asyouprogress,thebookdelvesintotheadministrativeaspectsofGrafanabycreatingalerts,settingpermissionsforteams,andimplementinguserauthentication.AlongwithexploringGrafana'smulti-cloudmonitoringsupport,you'llalsolearnaboutGrafanaLoki,whichisabackendloggerforusersrunningPrometheusandKubernetes.Bytheendofthisbook,you'llhavegainedalltheknowledgeyouneedtostartbuildinginteractivedashboards.

Eric Salituro ·自動化 ·7.6萬字

Learning RSLogix 5000 Programming
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Learning RSLogix 5000 Programming

Understandingprogrammablelogiccontroller(PLC)programmingwithRockwellSoftware’sLogixDesignerandtheStudio5000platform,whichincludesControlLogix,CompactLogix,andSoftLogix,iskeytobuildingrobustPLCsolutions.RSLogix5000/Studio5000’sLogixDesignerareuser-friendlyIEC61131-3-compliantinterfacesforprogrammingthecurrentgenerationofRockwellAutomationControllersusingLadderDiagram(LD),FunctionBlockDiagram(FBD),StructuredText(ST),andSequentialFunctionChart(SFC).ThissecondeditionofLearningRSLogix5000ProgrammingguidesyouthroughthetechnicalitiesandcomespackedwiththelatestfeaturesofStudio5000,industrialnetworkingfundamentals,andindustrialcybersecuritybestpractices.You’llgothroughtheessentialhardwareandsoftwarecomponentsofLogix,beforelearningallaboutthenewL8processormodelandthelatestStudio5000architecturetobuildeffectiveintegratedsolutions.Entirelynewforthisedition,you’lldiscoverachapteroncybersecurityconceptswithRSLogix5000.Thebookevengetsyouhands-onwithbuildingarobotbartendercontrolsystemfromstarttofinish.BytheendofthisLogix5000book,you’llhaveaclearunderstandingofthecapabilitiesoftheLogixplatformandbeabletoconfidentlynavigateRockwellAutomationLiteratureLibraryresources.

Austin Scott ·自動化 ·6.9萬字

QQ閱讀手機版

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