DiscoverhowempiricalresearcherstodayactuallyconsiderandapplyeconometricmethodswiththepracticalapproachinWooldridge'sINTRODUCTORYECONOMETRICS:AMODERNAPPROACH,6E.Unliketraditionaltexts,thisbookuniquelydemonstrateshoweconometricshasmovedbeyondasetofabstracttoolstobecomegenuinelyusefulforansweringquestionsinbusiness,policyevaluation,andforecasting.INTRODUCTORYECONOMETRICSisorganizedaroundthetypeofdatabeinganalyzedwithasystematicapproachthatonlyintroducesassumptionsastheyareneeded.Thismakesthematerialeasiertounderstandand,ultimately,leadstobettereconometricpractices.Packedwithrelevantapplications,thetextincorporatesmorethan100intriguingdatasets,availableinsixformats.Updatesintroducethelatestemergingdevelopmentsinthefield.GainafullunderstandingoftheimpactofeconometricsinpracticetodaywiththeinsightsandapplicationsfoundonlyinINTRODUCTORYECONOMETRICS:AMODERNAPPROACH,6E.

著名的Netflix智能推荐百万美金大奖赛使用是数据集.因为竞赛关闭,Netflix官网上已无法下载.Netflixprovidedatrainingdatasetof100,480,507ratingsthat480,189usersgaveto17,770movies.Eachtrainingratingisaquadrupletoftheform.TheuserandmoviefieldsareintegerIDs,whilegradesarefrom1to5(integral)stars.[3]Thequalifyingdatasetcontainsover2,817,131tripletsoftheform,withgradesknownonlytothejury.Aparticipatingteam'salgorithmmustpredictgradesontheentirequalifyingset,buttheyareonlyinformedofthescoreforhalfofthedata,thequizsetof1,408,342ratings.Theotherhalfisthetestsetof1,408,789,andperformanceonthisisusedbythejurytodeterminepotentialprizewinners.Onlythejudgesknowwhichratingsareinthequizset,andwhichareinthetestset—thisarrangementisintendedtomakeitdifficulttohillclimbonthetestset.Submittedpredictionsarescoredagainstthetruegradesintermsofrootmeansquarederror(RMSE),andthegoalistoreducethiserrorasmuchaspossible.Notethatwhiletheactualgradesareintegersintherange1to5,submittedpredictionsneednotbe.Netflixalsoidentifiedaprobesubsetof1,408,395ratingswithinthetrainingdataset.Theprobe,quiz,andtestdatasetswerechosentohavesimilarstatisticalproperties.Insummary,thedatausedintheNetflixPrizelooksasfollows:Trainingset(99,072,112ratingsnotincludingtheprobeset,100,480,507includingtheprobeset)Probeset(1,408,395ratings)Qualifyingset(2,817,131ratings)consistingof:Testset(1,408,789ratings),usedtodeterminewinnersQuizset(1,408,342ratings),usedtocalculateleaderboardscoresForeachmovie,titleandyearofreleaseareprovidedinaseparatedataset.Noinformationatallisprovidedaboutusers.Inordertoprotecttheprivacyofcustomers,"someoftheratingdataforsomecustomersinthetrainingandqualifyin

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-------目录第1章P神经网络的数据分类——语音特征信号分类第2章BP神经网络的非线性系统建模——非线性函数拟合第3章遗传算法优化BP神经网络——非线性函数拟合第4章神经网络遗传算法函数极值寻优——非线性函数极值寻优第5章基于BP_Adaboost的强分类器设计——公司财务预警建模第6章PID神经元网络解耦控制算法——多变量系统控制第7章RBF网络的回归——非线性函数回归的实现第8章GRNN的数据预测——基于广义回归神经网络的货运量预测第9章离散Hopfield神经网络的联想记忆——数字识别第10章离散Hopfield神经网络的分类——高校科研能力评价第11章连续Hopfield神经网络的优化——旅行商问题优化计算第12章SVM的数据分类预测——意大利葡萄酒种类识别第13章SVM的参数优化——如何更好的提升分类器的性能第14章SVM的回归预测分析——上证指数开盘指数预测第15章SVM的信息粒化时序回归预测——上证指数开盘指数变化趋势和变化空间预测第16章自组织竞争网络在模式分类中的应用——患者癌症发病预测第17章SOM神经网络的数据分类——柴油机故障诊断第18章Elman神经网络的数据预测——电力负荷预测模型研究第19章概率神经网络的分类预测——基于PNN的变压器故障诊断第20章神经网络变量筛选——基于BP的神经网络变量筛选第21章LVQ神经网络的分类——乳腺肿瘤诊断第22章LVQ神经网络的预测——人脸朝向识别第23章小波神经网络的时间序列预测——短时交通流量预测第24章模糊神经网络的预测算法——嘉陵江水质评价第25章广义神经网络的聚类算法——网络入侵聚类第26章粒子群优化算法的寻优算法——非线性函数极值寻优第27章遗传算法优化计算——建模自变量降维第28章基于灰色神经网络的预测算法研究——订单需求预测第29章基于Kohonen网络的聚类算法——网络入侵聚类第30章神经网络GUI的实现——基于GUI的神经网络拟合、模式识别、聚类MATLAB

Theupdatedrevisionofthewell-respectedbookonanalyzingaircraftperformance,ThisSecondEditionofthebestsellingAircraftControlandSimulationhasbeenexpandedandupdatedtoincludethelatesttechnologicaladvancesinthefield.Inaddition,anewsectiononbasicaerodynamics,aircraftconfiguration,andstaticstabilitymakesthiscomplexmaterialmoreaccessibletobeginners.,Thiscomprehensiveguidediscussesthefundamentalprinciplesandtheoryofaircraftcontrolandsimulation.Italsocoversmodelinganddynamicanalysis,stabilityevaluation,multivariablecontroltheory,andcomputer-aideddesigntechniques.Theinclusionoftopicsfromgeodesyandgravitationlaysthegroundworkforadiscussionofthetheoryforsuborbitalaircraftnowunderdevelopment.,Specialfeaturesofthisneweditioninclude:,*NewandupdatedcomputercalculationsusingMATLAB(r),*Anewsectiononbasicaerodynamics,aircraftconfigurations,andstaticstability,*CoverageofnewMIMOdesigntechniques,robustnesstheory,andnonlineardesign,Completewithexamplesofactualdesignsfromtheaircraftindustryplusexerciseproblems,AircraftControlandSimulation,SecondEditionisanexcellentreferenceforanyoneinvolvedinthedesignandmodelingofaerospacevehiclesandanoutstandingtextforbothundergraduatesandgraduatestudents.

Thisdefinitivetextbookprovidesasolidintroductiontodiscreteandcontinuousstochasticprocesses,tacklingacomplexfieldinawaythatinstilsadeepunderstandingoftherelevantmathematicalprinciples,anddevelopsanintuitivegraspofthewaytheseprinciplescanbeappliedtomodellingreal-worldsystems.ItincludesacarefulreviewofelementaryprobabilityanddetailedcoverageofPoisson,GaussianandMarkovprocesseswithrichlyvariedqueuingapplications.Thetheoryandapplicationsofinference,hypothesistesting,estimation,randomwalks,largedeviations,martingalesandinvestmentsaredeveloped.Writtenbyoneoftheworld'sleadinginformationtheorists,evolvingovertwentyyearsofgraduateclassroomteachingandenrichedbyover300exercises,thisisanexceptionalresourceforanyonelookingtodeveloptheirunderstandingofstochasticprocesses.

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DifferentialEquationsandLinearAlgebra(4th)英文无水印原版pdf第4版pdf所有页面使用FoxitReader、PDF-XChangeViewer、SumatraPDF和Firefox测试都可以打开本资源转载自网络，如有侵权，请联系上传者或csdn删除查看此书详细信息请在美国亚马逊官网搜索此书EditorialDirector,Mathematics:ChristinehoagEditor-in-Chief:DeirdreLynchAcquisitionsEditor:WilliamHoffmaProjectTeamLead:ChristinaleProjectmanager:LaurenMorseEditorialAssistant:JenniferSnyderProgramTeamLead:KarenwernholmProgramManagerDaniellesimbajonCoverandillustrationDesign:StudioMontageProgramDesignLead:BethPaquinProductMarketingManagerClaireKozarProductMarketingCoordiator:BrookesmithFieldMarketingManager:EvanStCyrSeniorAuthorSupport/TechnologySpecialist:JoevetereSeniorProcurementSpecialist:CarolMelvilleInteriorDesign,ProductionManagement,AnswerArt,andCompositioneNergizerAptara,LtdCoverImage:LighttrailsonmodernbuildingbackgroundinShanghai,China-hxdyl/123RFCopyrightO2017,2011,2005PearsonEducation,Inc.oritsaffiliates.AllRightsReserved.PrintedintheUnitedStatesofAmerica.Thispublicationisprotectedbycopyright,andpermissionshouldbeobtainedfromthepublisherpriortoanyprohibitedreproduction,storageinaretrievalsystem,ortransmissioninanyformorbyanymeans,electronic,mechanical,photocopyingrecording,orotherwise.Forinformationregardingpermissions,requestformsandtheappropriatecontactswithinthePearsonEducationGlobalRights&Permissionsdepartmentpleasevisitwww.pearsoned.com/permissions/PEARSONandALWAYSLEARNINGareexclusivetrademarksintheU.s.and/orothercountriesownedbyPearsonEducation,Inc.oritsaffiliatesUnlessotherwiseindicatedherein,anythird-partytrademarksthatmayappearinthisworkarethepropertyoftheirrespectiveowandanyreferencestothird-partytrademarks,logosorothertradedressarefordemonstrativeordescriptivepurposesonly.SuchofsuchmarksoranyrelationshipbetweentheownerandPearsonEducation,Inc.oritsaffiliates,authors,licenseesordistributortreferencesarenotintendedtoimplyanysponsorship,endorsement,authorization,orpromotionofPearsonsproductsbytheownersLibraryofCongressCataloging-in-PublicationDataGoode.StephenwDifferentialequationsandlinearalgebra/StephenW.GoodeandScottA.AnninCaliforniastateUniversity,Fullerton.-4theditionpagescmIncludesindexISBN978-0-321-96467-0—ISBN0-32196467-51.Differentialequations.2.Algebras,Linear.I.Annin,Scott.II.TitleQA371.G6442015515’.35-dc23201400601512345678910V031-1918171615PEARSONISBN10:0-321-96467-5www.pearsonhighered.comISBN13:978-0-321-96467-0ContentsPrefacevii1First-OrderDifferentialEquations1.1DifferentialEquationsEverywhere11.2BasicIdeasandTerminology131.3TheGeometryofFirst-OrderDifferentialEquations231.4SeparableDifferentialEquations341.5SomeSimplePopulationModels451.6First-OrderLinearDifferentialEquations531.7ModelingProblemsUsingFirst-OrderLinearDifferentialEquations61.8Changeofvariables711.9ExactDifferentialEquations821.10Numericalsolutiontofirst-OrderDifferentialEquations931.11SomeHigher-OrderDifferentialEquations1011.12ChapterReview1062MatricesandSystemsofLinearEquations1142.1Matrices:Definitionsandnotation1152.2MatrixAlgebra1222.3TerminologyforSystemsofLinearEquations13824R。
w-EchelonMatricesandElementaryR。
wOperations1462.5Gaussianelimination1562.6TheInverseofasquarematrix1682.7ElementaryMatricesandtheLUFactorization1792.8TheInvertiblematrixtheoremi1882.9ChapterReview1903Determinants1963.1TheDefinitionofthedeterminant1963.2PropertiesofDeterminants2093.3CofactorExpansions2223.4SummaryofDeterminants2353.5ChapterReview242iyContents4VectorSpaces2464.1Vectorsinrn2484.2DefinitionofaVectorSpace2524.3Subspaces2634.4SpanningSets2744.5LinearDependenceandLinearIndependence2844.6Basesanddimension2984.7Changeofbasis3114.8RowSpaceandColumnSpace3194.9TheRank-NullityTheorem3254.10InvertibleMatrixTheoremll3314.11ChapterReview3325InnerProductSpaces3395.1DefinitionofanInnerproductspace3405.2OrthogonalSetsofvectorsandorthogonalProjections3525.3Thegram-Schmidtprocess3625.4LeastSquaresApproximation3665.5ChapterReview3766LinearTransformations3796.1Definitionofalineartransformation3806.2Transformationsofr23916.3TheKernelandrangeofalineartransformation3976.4AdditionalPropertiesofLinearTransformations4076.5Thematrixofalineartransformation4196.6Chaiterreview4287EigenvaluesandEigenvectors4337.1TheEigenvalue/EigenvectorProblem4347.2GeneralResultsforEigenvaluesandEigenvectors4467.3Diagonalization4547.4AnIntroductiontotheMatrixExponentialFunction4627.5OrthogonalDiagonalizationandQuadraticforms4667.6Jordancanonicalforms4757.7Chapterreview4888LinearDifferentialEquationsofOrdern4938.1GeneralTheoryforLinearDifferentialEquations4958.2ConstantCoefficientHomogeneousLinearDifferentialEquations5058.3ThemethodofundeterminedcoefficientsAnnihilators5158.4Complex-ValuedTrialSolutions5268.5OscillationsofaMechanicalSystem529Contentsv8.6RLCCircuits5428.7TheVariationofparametersmethod5478.8ADifferentialEquationwithNonconstantCoefficients5578.9Reductionoforder5688.10ChapterReview5739SystemsofDifferentialEquations5809.1First-OrderLinearSystems5829.2VectorFormulation5889.3GeneralResultsforfirst-OrderLinearDifferentialystems5939.4VectorDifferentialEquations:NondefectiveCoefficientMatrix5999.5VectorDifferentialEquations:DefectiveCoefficientMatrix6089.6Variation-of-ParametersforLinearSystems6209.7SomeApplicationsofLinearSystemsofDifferentialEquations6259.8MatrixExponentialFunctionandSystemsofDifferentialEquations6359.9ThePhasePlaneforLinearAutonomousSystems6439.10NonlinearSystems6559.11ChapterReview66310TheLaplaceTransformandSomeElementaryApplications67010.1DefinitionoftheLaplaceTransform67010.2TheExistenceofthelaplacetransformandtheInversetransform67610.3PeriodicFunctionsandtheLaplacetransform68210.4ThetransformofderivativesandsolutionofInitial-Valueproblems68510.5TheFirstShiftingTheorem69010.6TheUnitStepFunction69510.7TheSecondShiftingTheorem69910.8ImpulsiveDrivingTerms:TheDiracDeltaFunction70610.9TheConvolutionIntegral71110.10ChapterReview71711SeriesSolutionstoLinearDifferentiaEquations72211.1AReviewofpowerseries72311.2SeriesSolutionsaboutanOrdinaryPoint73111.3TheLegendreEquation74111.4SeriesSolutionsaboutaRegularSingularPoint75011.5Frobeniustheory75911.6Bessel'sEquationofOrderp77311.7Chapterreview785ViContentsAReviewofComplexNumbers791BReviewofPartialFractions797CReviewofIntegrationTechniques804DLinearlyIndependentSolutionstox2y+xp(x)y+g(x)y=0811Answerstoodd-NumberedExercises814Index849S.W.GoodededicatesthisbooktomeganandtobiS.A.annindedicatesthisbooktoarthurandJuliannthebestparentsanyonecouldaskforPretraceLikethefirstthreeeditionsofDifferentialEquationsandLinearalgebra,thisfourtheditionisintendedforasophomorelevelcoursethatcoversmaterialinbothdifferentialequationsandlinearalgebra.Inwritingthistextwehaveendeavoredtodevelopthestudentsappreciationforthepowerofthegeneralvectorspaceframeworkinformulatingandsolvinglinearproblems.Thematerialisaccessibletoscienceandengineeringstu-dentswhohavecompletedthreesemestersofcalculusandwhobringthematurityofthatsuccesswiththemtothiscourseThistextiswrittenaswewouldnaturallyteachblendinganabundanceofexamplesandillustrations,butnotattheexpenseofadeliberateandrigoroustreatment.MostresultsareprovenindetailHowever,manyofthesecanbeskippedinfavorofamoreproblem-solvingorientedapproachdependingonthereader'sobjectives.Somereadersmayliketoincorporatesomeformoftechnology(computeralgebrasystem(CAS)orgraphingcalculator)andthereareseveralinstancesinthetextwherethepoweroftechnologyisillustratedusingtheCasMaple.Furthermore,manyexercisesetshaveproblemsthatrequiresomeformoftechnologyfortheirsolutionTheseproblemsaredesignatedwithaoIndevelopingthefourtheditionwehaveoncemorekeptmaximumflexibilityofthematerialinmind.Insodoing,thetextcaneffectivelyaccommodatethedifferentemphasesthatcanbeplacedinacombineddifferentialequationsandlinearalgebracourse,thevaryingbackgroundsofstudentswhoenrollinthistypeofcourse,andthefactthatdifferentinstitutionshavedifferentcreditvaluesforsuchacourse.Thewholetextcanbecoveredinafivecredit-hourcourse.Forcourseswithalowercredit-hourvalue,someselectivitywillhavetobeexercised.Forexample,much(orall)ofChapterImaybeomittedsincemoststudentswillhaveseenmanyofthesedifferentialequationstopicsinanearliercalculuscourse,andtheremainderofthetextdoesnotdependonthetechniquesintroducedinthischapter.Alternatively,whileoneofthemajorgoalsofthetextistointerweavethematerialondifferentialequationswiththetoolsfromlinearalgebrainasymbioticrelationshipasmuchaspossible,thecorematerialonlinearalgebraisgiveninChapters2-7sothatitispossibletousethisbookforacoursethatfocusessolelyonthelinearalgebrapresentedinthesesixchapters.ThematerialondifferentialequationsiscontainedprimarilyinChapters1and8-1l,andreaderswhohavealreadytakenafirstcourseinlinearalgebracanchoosetoproceeddirectlytothesechaptersThereareothermeansofeliminatingsectionstoreducetheamountofmaterialtobecoveredinacourse.Section2.7containsmaterialthatisnotrequiredelsewhereinthetext,Chapter3canbecondensedtoasinglesection(Section3.4)forreadersneedingonlyacursoryoverviewofdeterminants,andSections4.7,5.4,andthelatersectionsofChapters6and7couldallbereservedforasecondcourseinlinearalgebra.InChapter8Sections8.4,8.8,and8.9canbeomitted,and,dependingonthegoalsofthecourse,Sections8.5and8.6couldeitherbede-emphasizedoromittedcompletelySimilarremarksapplytoSections9.7-9.10.AtCaliforniaStateUniversity,Fullertonwehaveafourcredit-hourcourseforsophomoresthatisbasedaroundthematerialinChapters1-9viiiPrefaceMajorChangesintheFourthEditionSeveralsectionsofthetexthavebeenmodifiedtoimprovetheclarityofthepresentationandtoprovidenewexamplesthatreflectinsightfulillustrationswehaveusedinourowncoursesatCaliforniaStateUniversity,Fullerton.OthersignificantchangeswithinthetextarelistedbeleOW1.ThechapteronvectorspacesinthepreviouseditionhasbeensplitintotwochaptersChapters4and5)inthepresentedition,inordertofocusseparateattentiononvectorspacesandinnerproductspaces.Theshorterlengthofthesetwochaptersisalsointendedtomakeeachofthemlessdaunting2.Thechapteroninnerproductspaces(Chapter5)includesanewsectionprovidinganapplicationoflinearalgebratothesubjectofleastsquaresapproximation3.Thechapteronlineartransformationsinthepreviouseditionhasbeensplitintotwochapters(Chapters6and7)inthepresentedition.Chapter6isfocusedonlineartransformations,whileChapter7placesdirectemphasisonthetheoryofeigenvaluesandeigenvectors.Oncemore,readersshouldfindtheshorterchapterscoveringthesetopicsmoreapproachableandfocused4.Mostexercisesetshavebeenenlargedorrearranged.Over3,000problemsarenowcontainedwithinthetext,andmorethan600concept-orientedtrue/falseitemsarealsoincludedinthetext5.Everychapterofthebookincludesoneormoreoptionalprojectsthatallowformorein-depthstudyandapplicationofthetopicsfoundinthetext6.ThebackofthebooknowincludestheanswertoeveryTrue-FalsereviewitemcontainedinthetextAcknowledgmentsWewouldliketoacknowledgethethoughtfulinputfromthefollowingreviewersofthefourthedition:JameyBassofCityCollegeofSanFrancisco,TamarFriedmannofUniversityofrochester,andlinghaiZhangofLehighUniversityAlloftheircommentswereconsideredcarefullyinthepreparationofthetextS.A.Annin:Ioncemorethankmyparents,ArthurandJuliannAnnin,fortheirloveandencouragementinallofmyprofessionalendeavors.Ialsogratefullyacknowledgethemanystudentswhohavetakenthiscoursewithmeovertheyearsand,insodoinghaveenhancedmyloveforthesetopicsanddeeplyenrichedmycareerasaprofessorFirst-OrderDifferentiaEquations1.1DifferentialEquationsEverywhereadifferentialequationisanyequationthatinvolvesoneormorederivativesofanunknownfunction.Forexample(1.1.1dxds(S-1)(1.1.2)aredifferentialequations.Inthedifferentialequation(1.1.1)theunknownfunctionordependentvariableisy,andxistheindependentvariable;inthedifferentialequation(1.1.2)thedependentandindependentvariablesareSandt,respectively.Differentialequationssuchas(1.1.1)and(1.1.)inwhichtheunknownfunctiondependsonlyonasingleindependentvariablearecalledordinarydifferentialequations.Bycontrast,thedifferentialequationLaplace'sequation)0involvespartialderivativesoftheunknownfunctionu(x,y)oftwoindependentvariablesxandy.SuchdifferentialequationsarecalledpartialdifferentialequationsOnewayinwhichdifferentialequationscanbecharacterizedisbytheorderofthehighestderivativethatoccursinthedifferentialequationThisnumberiscalledtheorderofthedifferentialequation.Thus,(l1.1)hasordertwo,whereas(1.1.2)isafirst-orderdifferentialequation1

Writtenbypioneersoftheconcept,thisisthefirstcompleteguidetothephysicalandengineeringprinciplesofMassiveMIMO.Assumingonlyabasicbackgroundincommunicationsandstatisticalsignalprocessing,itwillguidereadersthroughkeytopicssuchaspropagationmodels,channelmodeling,andmulti-cellperformanceanalyses.Theauthors’uniquecapacity-boundapproachwillenablereaderstocarryoutmoreeffectivesystemperformanceanalysisanddevelopadvancedMassiveMIMOtechniquesandalgorithms.Numerouscasestudies,aswellasproblemsetsandsolutionsaccompanyingthebookonline,willhelpreadersputknowledgeintopracticeandacquiretheskillsetneededtodesignandanalyzecomplexwirelesscommunicationsystems.Whetheryouareagraduatestudent,researcher,orindustryprofessionalworkinginthefieldofwirelesscommunications,thiswillbeanindispensableguideforyearstocome.

Deeplearningdoesn'thavetobeintimidating.Untilrecently,thismachine-learningmethodrequiredyearsofstudy,butwithframeworkssuchasKerasandTensorflow,softwareengineerswithoutabackgroundinmachinelearningcanquicklyenterthefield.Withtherecipesinthiscookbook,you'lllearnhowtosolvedeep-learningproblemsforclassifyingandgeneratingtext,images,andmusic.Eachchapterconsistsofseveralrecipesneededtocompleteasingleproject,suchastrainingamusicrecommendingsystem.AuthorDouweOsingaalsoprovidesachapterwithhalfadozentechniquestohelpyouifyou'restuck.ExamplesarewritteninPythonwithcodeavailableonGitHubasasetofPythonnotebooks.You'lllearnhowto:CreateapplicationsthatwillserverealusersUsewordembeddingstocalculatetextsimilarityBuildamovierecommendersystembasedonWikipedialinksLearnhowAIsseetheworldbyvisualizingtheirinternalstateBuildamodeltosuggestemojisforpiecesoftextReusepretrainednetworkstobuildaninverseimagesearchserviceComparehowGANs,autoencodersandLSTMsgenerateiconsDetectmusicstylesandindexsongcollections

在日常工作中，钉钉打卡成了我生活中不可或缺的一部分。然而，有时候这个看似简单的任务却给我带来了不少烦恼。 每天早晚，我总是得牢记打开钉钉应用，点击"工作台"，再找到"考勤打卡"进行签到。有时候因为工作忙碌，会忘记打卡，导致考勤异常，影响当月的工作评价。而且，由于我使用的是苹果手机，有时候系统更新后，钉钉的某些功能会出现异常，使得打卡变得更加麻烦。 另外，我的家人使用的是安卓手机，他们也经常抱怨钉钉打卡的繁琐。尤其是对于那些不太熟悉手机操作的长辈来说，每次打卡都是一次挑战。他们总是担心自己会操作失误，导致打卡失败。 为了解决这些烦恼，我开始思考是否可以通过编写一个全自动化脚本来实现钉钉打卡。经过一段时间的摸索和学习，我终于成功编写出了一个适用于苹果和安卓系统的钉钉打卡脚本。