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Azure Serverless Computing Cookbook
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Azure Serverless Computing Cookbook

MicrosoftprovidesasolutionforeasilyrunningsmallsegmentsofcodeinthecloudwithAzureFunctions.ThesecondeditionofAzureServerlessComputingCookbookstartswithintermediate-levelrecipesonserverlesscomputingalongwithsomeusecasesdemonstratingthebenefitsandkeyfeaturesofAzureFunctions.You’llexplorethecoreaspectsofAzureFunctions,suchastheservicesitprovides,howyoucandevelopandwriteAzureFunctions,andhowtomonitorandtroubleshootthem.Asyoumakeyourwaythroughthechapters,you’llgetpracticalrecipesonintegratingDevOpswithAzureFunctions,andprovidingcontinuousintegrationandcontinuousdeploymentwithAzureDevOps.Thisbookalsoprovideshands-on,step-by-steptutorialsbasedonreal-worldserverlessusecasestoguideyouthroughconfiguringandsettingupyourserverlessenvironmentswithease.Youwillalsolearnhowtobuildsolutionsforcomplex,real-world,workflow-basedscenariosquicklyandwithminimalcodeusingDurableFunctions.Intheconcludingchapters,youwillensureenterprise-levelsecuritywithinyourserverlessenvironment.ThemostcommontipsandtricksthatyouneedtobeawareofwhenworkingwithAzureFunctionsonproductionenvironmentswillalsobecoveredinthisbook.Bytheendofthisbook,youwillhavealltheskillsrequiredforworkingwithserverlesscodearchitecture,providingcontinuousdeliverytoyourusers.

Praveen Kumar Sreeram ·自動化 ·5.1萬字

Mastering Windows Group Policy
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Mastering Windows Group Policy

ThisbookbeginswithadiscussionofthecorematerialanyadministratorneedstoknowinordertostartworkingwithGroupPolicy.Movingon,wewillalsowalkthroughtheprocessofbuildingalabenvironmenttostarttestingGroupPolicytoday.NextwewillexploretheGroupPolicyManagementConsole(GPMC)andstartusingthepowerfulfeaturesavailableforuswithinthatinterface.OnceyouarewellversedwithusingGPMC,youwilllearntoperformandmanagethetraditionalcoretasksinsideGroupPolicy.Includedinthebookaremanyexamplesandwalk-throughsofthedifferentfilteringoptionsavailablefortheapplicationofGroupPolicysettings,asthisistherealpowerthatGroupPolicyholdswithinyournetwork.YouwillalsolearnhowyoucanuseGroupPolicytosecureyourActiveDirectoryenvironment,andalsounderstandhowGroupPolicypreferencesaredifferentthanpolicies,withthehelpofreal-worldexamples.FinallywewillspendsometimeonmaintenanceandtroubleshootingcommonGroupPolicy-relatedissuessothatyou,asadirectoryadministrator,willunderstandthediagnosingprocessforpolicysettings.Bytheendofthebook,youwillbeabletojumprightinanduseGroupPolicytoitsfullpotential.

Jordan Krause ·自動化 ·8.7萬字

Apache Superset Quick Start Guide
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Apache Superset Quick Start Guide

ApacheSupersetisamodern,opensource,enterprise-readybusinessintelligence(BI)webapplication.Withthehelpofthisbook,youwillseehowSupersetintegrateswithpopulardatabaseslikePostgres,GoogleBigQuery,Snowflake,andMySQL.YouwilllearntocreaterealtimedatavisualizationsanddashboardsonmodernwebbrowsersforyourorganizationusingSuperset.First,welookatthefundamentalsofSuperset,andthengetitupandrunning.You'llgothroughtherequisiteinstallation,configuration,anddeployment.Then,wewilldiscussdifferentcolumnardatatypes,analytics,andthevisualizationsavailable.You'llalsoseethesecuritytoolsavailabletotheadministratortokeepyourdatasafe.Youwilllearnhowtovisualizerelationshipsasgraphsinsteadofcoordinatesonplainorthogonalaxes.Thiswillhelpyouwhenyouuploadyourownentityrelationshipdatasetandanalyzethedatasetinnew,differentways.Youwillalsoseehowtoanalyzegeographicalregionsbyworkingwithlocationdata.Finally,wecoverasetoftutorialsondashboarddesignsfrequentlyusedbyanalysts,businessintelligenceprofessionals,anddevelopers.

Shashank Shekhar ·自動化 ·2.2萬字

Microsoft Power BI Complete Reference
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Microsoft Power BI Complete Reference

MicrosoftPowerBICompleteReferenceGuidegetsyoustartedwithbusinessintelligencebyshowingyouhowtoinstallthePowerBItoolset,designeffectivedatamodels,andbuildbasicdashboardsandvisualizationsthatmakeyourdatacometolife.InthisLearningPath,youwilllearntocreatepowerfulinteractivereportsbyvisualizingyourdataandlearnvisualizationstyles,tipsandtrickstobringyourdatatolife.Youwillbeabletoadministeryourorganization'sPowerBIenvironmenttocreateandsharedashboards.Youwillalsobeabletostreamlinedeploymentbyimplementingsecurityandregulardatarefreshes.Next,youwilldelvedeeperintothenuancesofPowerBIandhandlingprojects.YouwillgetacquaintedwithplanningaPowerBIproject,development,anddistributionofcontent,anddeployment.Youwilllearntoconnectandextractdatafromvarioussourcestocreaterobustdatasets,reports,anddashboards.Additionally,youwilllearnhowtoformatreportsandapplycustomvisuals,animationandanalyticstofurtherrefineyourdata.BytheendofthisLearningPath,youwilllearntoimplementthevariousPowerBItoolssuchason-premisesgatewaytogetheralongwithstagingandsecurelydistributingcontentviaapps.ThisLearningPathincludescontentfromthefollowingPacktproducts:MicrosoftPowerBIQuickStartGuidebyDevinKnightetal.MasteringMicrosoftPowerBIbyBrettPowell.

Devin Knight Brian Knight Mitchell Pearson Manuel Quintana Brett Powell ·自動化 ·17.8萬字

Machine Learning with Apache Spark Quick Start Guide
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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.

Jillur Quddus ·自動化 ·5.2萬字

Bayesian Analysis with Python
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Bayesian Analysis with Python

ThesecondeditionofBayesianAnalysiswithPythonisanintroductiontothemainconceptsofappliedBayesianinferenceanditspracticalimplementationinPythonusingPyMC3,astate-of-the-artprobabilisticprogramminglibrary,andArviZ,anewlibraryforexploratoryanalysisofBayesianmodels.ThemainconceptsofBayesianstatisticsarecoveredusingapracticalandcomputationalapproach.Syntheticandrealdatasetsareusedtointroduceseveraltypesofmodels,suchasgeneralizedlinearmodelsforregressionandclassification,mixturemodels,hierarchicalmodels,andGaussianprocesses,amongothers.Bytheendofthebook,youwillhaveaworkingknowledgeofprobabilisticmodelingandyouwillbeabletodesignandimplementBayesianmodelsforyourowndatascienceproblems.Afterreadingthebookyouwillbebetterpreparedtodelveintomoreadvancedmaterialorspecializedstatisticalmodelingifyouneedto.

Osvaldo Martin ·自動化 ·8.6萬字

Hands-On Predictive Analytics with Python
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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.

Alvaro Fuentes ·自動化 ·7.1萬字

Practical Network Automation
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Practical Network Automation

NetworkautomationistheuseofITcontrolstosuperviseandcarryouteverydaynetworkmanagementfunctions.Itplaysakeyroleinnetworkvirtualizationtechnologiesandnetworkfunctions.Thebookstartsbyprovidinganintroductiontonetworkautomation,anditsapplications,whichincludeintegratingDevOpstoolstoautomatethenetworkefficiently.Itthenguidesyouthroughdifferentnetworkautomationtasksandcoversvariousdatadiggingandperformingtaskssuchasensuringgoldenstateconfigurationsusingtemplates,interfaceparsing.ThisbookalsofocusesonIntelligentOperationsusingArtificialIntelligenceandtroubleshootingusingchatbotsandvoicecommands.ThebookthenmovesontotheuseofPythonandthemanagementofSSHkeysformachine-to-machine(M2M)communication,allfollowedbypracticalusecases.ThebookalsocoverstheimportanceofAnsiblefornetworkautomation,includingbestpracticesinautomation;waystotestautomatednetworksusingtoolssuchasPuppet,SaltStack,andChef;andotherimportanttechniques.Throughpracticaluse-casesandexamples,thisbookwillacquaintyouwiththevariousaspectsofnetworkautomation.Itwillgiveyouthesolidfoundationyouneedtoautomateyourownnetworkwithoutanyhassle.

Abhishek Ratan ·自動化 ·3.5萬字

Blockchain Quick Start Guide
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Blockchain Quick Start Guide

Blockchainisatechnologythatpowersthedevelopmentofdecentralizedapplications.Thistechnologyallowstheconstructionofanetworkwithnosinglecontrolthatenablesparticipantstomakecontributionstoandreceivebenefitsfromthenetworkdirectly.Thisbookwillgiveyouathoroughoverviewofblockchainandexplainhowablockchainworks.Youwillbeginbygoingthroughvariousblockchainconsensusmechanismsandcryptographichashfunctions.YouwillthenlearnthefundamentalsofprogramminginSolidity–thedefactolanguagefordevelopingdecentralize,applicationsinEthereum.Afterthat,youwillsetupanEthereumdevelopmentenvironmentanddevelop,package,build,andtestcampaign-decentralizedapplications.ThebookalsoshowsyouhowtosetupHyperledgercomposertools,analyzebusinessscenarios,designbusinessmodels,andwriteachaincode.Finally,youwillgetaglimpseofhowblockchainisactuallyusedindifferentreal-worlddomains.Bytheendofthisguide,youwillbecomfortableworkingwithbasicblockchainframeworks,anddevelopsecure,decentralizedapplicationsinahassle-freemanner.

Xun (Brian) Wu Weimin Sun ·自動化 ·4.2萬字

Linux Administration Cookbook
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Linux Administration Cookbook

Linuxisoneofthemostwidelyusedoperatingsystemsamongsystemadministrators,andevenmodernapplicationandserverdevelopmentisheavilyreliantontheLinuxplatform.TheLinuxAdministrationCookbookisyourgo-toguidetogetstartedonyourLinuxjourney.Itwillhelpyouunderstandwhatthatstrangelittleserverisdoinginthecornerofyouroffice,whatthemysteriousvirtualmachinelanguishinginAzureiscrunchingthrough,whatthatcircuit-board-likethingisdoingunderyourofficeTV,andwhytheLEDsonitareblinkingrapidly.ThisbookwillgetyoustartedwithadministeringLinux,givingyoutheknowledgeandtoolsyouneedtotroubleshootday-to-dayproblems,rangingfromaRaspberryPitoaserverinAzure,whilegivingyouagoodunderstandingofthefundamentalsofhowGNU/Linuxworks.Throughthecourseofthebook,you’llinstallandconfigureasystem,whiletheauthorregalesyouwitherrorsandanecdotesfromhisvastexperienceasadatacenterhardwareengineer,systemsadministrator,andDevOpsconsultant.Bytheendofthebook,youwillhavegainedpracticalknowledgeofLinux,whichwillserveasabedrockforlearningLinuxadministrationandaidyouinyourLinuxjourney.

Adam K. Dean ·自動化 ·16.7萬字

Keras 2.x Projects
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Keras 2.x Projects

Keras2.xProjectsexplainshowtoleveragethepowerofKerastobuildandtrainstate-of-the-artdeeplearningmodelsthroughaseriesofpracticalprojectsthatlookatarangeofreal-worldapplicationareas.Tobeginwith,youwillquicklysetupadeeplearningenvironmentbyinstallingtheKeraslibrary.Througheachoftheprojects,youwillexploreandlearntheadvancedconceptsofdeeplearningandwilllearnhowtocomputeandrunyourdeeplearningmodelsusingtheadvancedofferingsofKeras.Youwilltrainfully-connectedmultilayernetworks,convolutionalneuralnetworks,recurrentneuralnetworks,autoencodersandgenerativeadversarialnetworksusingreal-worldtrainingdatasets.Theprojectsyouwillundertakeareallbasedonreal-worldscenariosofallcomplexitylevels,coveringtopicssuchaslanguagerecognition,stockvolatility,energyconsumptionprediction,fasterobjectclassificationforself-drivingvehicles,andmore.Bytheendofthisbook,youwillbewellversedwithdeeplearninganditsimplementationwithKeras.Youwillhavealltheknowledgeyouneedtotrainyourowndeeplearningmodelstosolvedifferentkindsofproblems.

Giuseppe Ciaburro ·自動化 ·9.6萬字

R Machine Learning Projects
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R Machine Learning Projects

Risoneofthemostpopularlanguageswhenitcomestoperformingcomputationalstatistics(statisticalcomputing)easilyandexploringthemathematicalsideofmachinelearning.Withthisbook,youwillleveragetheRecosystemtobuildefficientmachinelearningapplicationsthatcarryoutintelligenttaskswithinyourorganization.Thisbookwillhelpyoutestyourknowledgeandskills,guidingyouonhowtobuildeasilythroughtocomplexmachinelearningprojects.Youwillfirstlearnhowtobuildpowerfulmachinelearningmodelswithensemblestopredictemployeeattrition.Next,you’llimplementajokerecommendationengineandlearnhowtoperformsentimentanalysisonAmazonreviews.You’llalsoexploredifferentclusteringtechniquestosegmentcustomersusingwholesaledata.Inadditiontothis,thebookwillgetyouacquaintedwithcreditcardfrauddetectionusingautoencoders,andreinforcementlearningtomakepredictionsandwinonacasinoslotmachine.Bytheendofthebook,youwillbeequippedtoconfidentlyperformcomplextaskstobuildresearchandcommercialprojectsforautomatedoperations.

Dr. Sunil Kumar Chinnamgari ·自動化 ·7.1萬字

Hands-On Artificial Intelligence for IoT
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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.

Amita Kapoor ·自動化 ·7.5萬字

Machine Learning Quick Reference
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Machine Learning Quick Reference

Machinelearningmakesitpossibletolearnabouttheunknownsandgainhiddeninsightsintoyourdatasetsbymasteringmanytoolsandtechniques.Thisbookguidesyoutodojustthatinaverycompactmanner.Aftergivingaquickoverviewofwhatmachinelearningisallabout,MachineLearningQuickReferencejumpsrightintoitscorealgorithmsanddemonstrateshowtheycanbeappliedtoreal-worldscenarios.Frommodelevaluationtooptimizingtheirperformance,thisbookwillintroduceyoutothebestpracticesinmachinelearning.Furthermore,youwillalsolookatthemoreadvancedaspectssuchastrainingneuralnetworksandworkwithdifferentkindsofdata,suchastext,time-series,andsequentialdata.Advancedmethodsandtechniquessuchascausalinference,deepGaussianprocesses,andmorearealsocovered.Bytheendofthisbook,youwillbeabletotrainfast,accuratemachinelearningmodelsatyourfingertips,whichyoucaneasilyuseasapointofreference.

Rahul Kumar ·自動化 ·4.7萬字

Implementing AWS：Design，Build，and Manage your Infrastructure
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Implementing AWS：Design，Build，and Manage your Infrastructure

WiththisLearningPath,you’llexploretechniquestoeasilymanageapplicationsontheAWScloud.You’llbeginwithanintroductiontoserverlesscomputing,itsadvantages,andthefundamentalsofAWS.Thefollowingchapterswillguideyouonhowtomanagemultipleaccountsbysettingupconsolidatedbilling,enhancingyourapplicationdeliveryskills,withthelatestAWSservicessuchasCodeCommit,CodeDeploy,andCodePipelinetoprovidecontinuousdeliveryanddeployment,whilealsosecuringandmonitoringyourenvironment'sworkflow.It’llalsoaddtoyourunderstandingoftheservicesAWSLambdaprovidestodevelopers.Torefineyourskillsfurther,itdemonstrateshowtodesign,write,test,monitor,andtroubleshootLambdafunctions.BytheendofthisLearningPath,you’llbeabletocreateahighlysecure,fault-tolerant,andscalableenvironmentforyourapplications.ThisLearningPathincludescontentfromthefollowingPacktproducts:AWSAdministration:TheDefinitiveGuide,SecondEditionbyYohanWadia.AWSAdministrationCookbookbyRowanUdell,LucasChan.MasteringAWSLambdabyYohanWadia,UditaGupta.

Yohan Wadia Rowan Udell Lucas Chan Udita Gupta ·自動化 ·12.8萬字

Azure for Architects
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Azure for Architects

Overtheyears,Azurecloudserviceshavegrownquickly,andthenumberoforganizationsadoptingAzurefortheircloudservicesisalsograduallyincreasing.LeadingindustrygiantsarefindingthatAzurefulfillstheirextensivecloudrequirements.AzureforArchitects–SecondEditionstartswithanextensiveintroductiontomajordesigningandarchitecturalaspectsavailablewithAzure.Thesedesignpatternsfocusondifferentaspectsofthecloud,suchashighavailability,security,andscalability.Gradually,wemoveontootheraspects,suchasARMtemplatemodulardesignanddeployments.Thisistheageofmicroservicesandserverlessisthepreferredimplementationmechanismforthem.ThisbookcoverstheentireserverlessstackavailableinAzureincludingAzureEventGrid,AzureFunctions,andAzureLogicApps.Newandadvancefeatureslikedurablefunctionsarediscussedatlength.Acompleteintegrationsolutionusingtheseserverlesstechnologiesisalsopartofthebook.AcompletechapterdiscussesallpossibleoptionsrelatedtocontainersinAzureincludingAzureKubernetesservices,AzureContainerInstancesandRegistry,andWebAppforContainers.DatamanagementandintegrationisanintegralpartofthisbookthatdiscussesoptionsforimplementingOLTPsolutionsusingAzureSQL,BigDatasolutionsusingAzureDatafactoryandDataLakeStorage,eventingsolutionsusingstreamanalytics,andEventHubs.ThisbookwillprovideinsightsintoAzuregovernancefeaturessuchastagging,RBAC,costmanagement,andpolicies.Bytheendofthisbook,youwillbeabletodevelopafull-?edgedAzurecloudsolutionthatisEnterpriseclassandfuture-ready.

Ritesh Modi ·自動化 ·8.6萬字

Serverless Programming Cookbook
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Serverless Programming Cookbook

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.

Heartin Kanikathottu ·電子通信 ·8.1萬字

Generative Adversarial Networks Projects
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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.

Kailash Ahirwar ·自動化 ·5.2萬字

Ensemble Machine Learning Cookbook
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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.

Dipayan Sarkar Vijayalakshmi Natarajan ·自動化 ·5.5萬字

Ceph：Designing and Implementing Scalable Storage Systems
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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.

Michael Hackett Vikhyat Umrao Karan Singh Nick Fisk Anthony D'Atri Vaibhav Bhembre ·自動化 ·10.8萬字

QQ閱讀手機版

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