深度学习(DeepLearning)是机器学习(MachineLearning)中近年来备受重视的一支，深度学习根源于类神经网络(ArtificialNeuralNetwork)模型，但今日深度学习的技术和它的前身已截然不同，目前最好的语音识别和影像辨识系统都是以深度学习技术来完成，你可能在很多不同的场合听过各种用深度学习做出的惊人应用(例如：最近红遍大街小巷的AlphaGo)，听完以后觉得心痒痒的，想要赶快使用这项强大的技术，却不知要从何下手学习，可以学习一下这个资料。
可以毫不犹豫的说，这个资料是我看过最系统，也最通俗易懂的关于深度学习的文章。
它是由台大教授李宏毅讲解一天搞懂深度学习讲课的PPT，PPT主要包含四部分：什么是深度学习、深度学习的各种小技巧、有记忆力的深度学习模型、深度学习的应用和展望。
OutlineLectureI:IntroductionofDeepLearningLecturell:TipsforTrainingDeepNeuralNetworkLecturelll:ariantsofneuralNetworkLecturev:NextWaveLectureIntroductionofDeeplearningOutlineoflecturentroductionofDeepLearningLet'sstartwithgeneralmachinelearningWhyDeep"HelloWorldforDeepLearningMachineLearningLookingforafunctionSpeechrecognitionHowareyouImagerecognition=“Cat"Playinggo5-5″(nextmoveDialogueSystemHello(whattheusersaid)(systemresponseImageRecognition:FrameworkcatAsetofModefunctioncat)=“money"dosnakeImageRecognition:FrameworkcatAsetofModelf(41)="cat"f(=“moneyfunctionBetter)=“dog"f2(nakeGoodnessoffunctionfSupervisedLearningTrainingDatamonkey”“cat"“dogImageRecognition:FrameworkcatModelTrainingTestinAsetofunctioncatStepGoodnessofPickthe"Best"FunctionUsingfunctionfStepStep3TrainingDatamonkey”“cat"“dogThreestepsfordeeplearningStepStepStep3:pickdefineasetgoodnessofthebestoffunctionfunctionfunctionDeepLearningissosimple3DCTENCENTCO

著名的PDF编程插件16.13版本，带sn，支持Delphi10.3RioQuickPDFLibraryforWindowsActiveX–ActiveXCOMforWindowsdevelopmentsupportsC#,VisualC++,C++Builder,Delphi,VisualBasic,PHP,Python,Java,PowerBASICandmore.32-bitand64-bitversions.DLL–Dynamically-linkedlibraryforWindowsdevelopmentsupportsC,VisualC++,C++Builder,C#,VisualBasic,Pythonandmore.32-bitand64-bitversions.Delphi–DCUsandoptionallysourcecodefordevelopmentusingallversionsofDelphiincluding4,5,6,7,2005,2006,2007,2009,2010,XE,XE2,XE3,XE4,XE5,XE6,XE7,XE8,and10.2.32-bitand64-bitversions.LIB–Statically-linkedlibraryforWindowsdevelopmentsupportsCandC++.32-bitonly.64-bitcomingsoon.QuickPDFLibraryforMacDylib–XcodeDynamicLibraryforMacdevelopmentusingObjective-C,Swift,C,C++andPython.32-bitand64-bit.Delphi–DCUsfordevelopmentusingDelphiXE2,XE3,XE4,XE5,XE6,XE7,XE8,and10.2onWindowstogenerateappsfortheMacoperatingsystem.32-bitonly.QuickPDFLibraryforiOSiOSStaticLib–iOSStaticLibforAppleiOSdevelopmentusingObjective-C,Swift,C,C++andmore.32-bitand64-bit.QuickPDFLibraryforAndroidAndroidStaticandDynamicLib–Android(API15,Android4.0.3ornewer)StaticandDynamicLib.AndroidStudioandVisualStudiosamplesprovided.32-bitand64-bit.QuickPDFLibraryforLinuxLinux–64-bitoperatingsystemUbuntu–version16andlaterCentOS–version6andlaterDebian–version8andlater

DetailedStepsforDTIDataProcessing，FSL中DTI数据处理详细步骤TBSS

使用《自动化学报》或其他期刊latex模版时，如提示缺少psfig.sty则需要将这个文件添加到latex模版目录中。

基于MATLAB并结合IBD算法的盲迭代反卷积法进行图像复原图像复原盲迭代反卷积IBDPSF估计

计算机视觉3D点云经典书籍-Semantic3DObjectMapsforEverydayManipulationinHumanLivingEnvironments讲述了点云的几何计算原理以及利用点云特征FPHF进行匹配即分类用生活环境如厨房清理开门等实例进行了举例和讲解

Inresponsetotheexponentiallyincreasingneedtoanalyzevastamountsofdata,NeuralNetworksforAppliedSciencesandEngineering:FromFundamentalstoComplexPatternRecognitionprovidesscientistswithasimplebutsystematicintroductiontoneuralnetworks.Beginningwithanintroductorydiscussionontheroleofneuralnetworksinscientificdataanalysis,thisbookprovidesasolidfoundationofbasicneuralnetworkconcepts.Itcontainsanoverviewofneuralnetworkarchitecturesforpracticaldataanalysisfollowedbyextensivestep-by-stepcoverageonlinearnetworks,aswellas,multi-layerperceptronfornonlinearpredictionandclassificationexplainingallstagesofprocessingandmodeldevelopmentillustratedthroughpracticalexamplesandcasestudies.LaterchapterspresentanextensivecoverageonSelfOrganizingMapsfornonlineardataclustering,recurrentnetworksforlinearnonlineartimeseriesforecasting,andothernetworktypessuitableforscientificdataanalysis.Withaneasytounderstandformatusingextensivegraphicalillustrationsandmultidisciplinaryscientificcontext,thisbookfillsthegapinthemarketforneuralnetworksformulti-dimensionalscientificdata,andrelatesneuralnetworkstostatistics.FeaturesxExplainsneuralnetworksinamulti-disciplinarycontextxUsesextensivegraphicalillustrationstoexplaincomplexmathematicalconceptsforquickandeasyunderstanding?Examinesin-depthneuralnetworksforlinearandnonlinearprediction,classification,clusteringandforecastingxIllustratesallstagesofmodeldevelopmentandinterpretationofresults,includingdatapreprocessing,datadimensionalityreduction,inputselection,modeldevelopmentandvalidation,modeluncertaintyassessment,sensitivityanalysesoninputs,errorsandmodelparametersSandhyaSamarasingheobtainedherMScinMechanicalEngineeringfromLumumbaUniversityinRussiaandanMSandPhDinEngineeringfromVirginiaTech,USA.

本程序可解决，京瓷SF-1020MFPSF-1025更换主板或扫描头后，打印正常，复印字变大的问题本程序不支持WIN10，请用WIN7以下系统。
看到机器的型号与固件版本,点UPGRADE下载，看进度条跑到100%之后，打印机会自动重启。
然后电脑这下载的英文显示完成。
完成升级。
升级过程不要断电。
切记！

Thisbookintroducesyoutotheworldofdatastructuresandalgorithms.Datastructuredefinesthewaydataisarrangedincomputermemoryforfastandefficientaccesswhilealgorithmisasetofinstructiontosolveproblemsbymanipulatingthesedatastructures.DataStructuresalgorithmsInGoHemantjainCopyrightoHemantJain2017.AllRightReservedHemantJainassertsthemoralrighttobeidentifiedasheauthorofthisworkAllrightsreserved.Nopartofthispublicationmaybereproduced,storedinorintroducedintoaretrievalsystem,ortransmitted,inanyform,orbyanymeans(electrical,mechanical,photocopying,recordingorotherwise)withoutthepriorwrittenpermissionoftheauthor,exceptinthecaseofverybriefquotationsembodiedincriticalreviewsandcertainothernonco妹妹ercialusespermittedbycopyrightlaw.AnypersonwhodoesanyunauthorizedactinrelationtothispublicationmaybeliabletocriminalprosecutionandcivilclaimsfordamagesACKNOWLEDGEMENTTheauthorisverygratefultoGodALMIGhTYforhisgraceandblessingDeepestgratitudeforthehelpandsupportofmybrotherDrSumantJain.ThisbookwouldnothavebeenpossiblewithoutthesupportandencouragementheprovidedIwouldliketoexpressprofoundgratitudetomyguide/myfriendNaveenKaushikforhisinvaluableencouragement,supervisionandusefulsuggestionthroughoutthisbookwritingwork.hissupportandcontinuousguidanceenablemetocompletemyworksuccessfuFinallyyetimportantly,IamthankfultoLoveSinghal,AnilberryandotherswhohelpedmedirectlyorindirectlyincompletingthisbookHemantJainTABLEOFCONTENTSACKNOWLEDGEMENTTABLEOFCONTENTSChAPTERO:HOWTOUSETHISBOOKWHATTHISBOOKISABOUTPREPARATIONPLANSSUMMARYChAPTER1:NTRODUCTION-PROGRAMMIINGOVERVIEWINTRODUCTIONFIRSTGOPROGRAMvariablesconstantsBASICDATATYPESSTRINGCONDITIONSANDLOOPSFUNCTIONPARAMETERPASSINGCALLBYVALUEPOINTERSPARAMETERPASSING.CALLBYPOINTER/REFERENCESTRUCTURESMETHODSINTERFACEARRaySLICEMAP/DICTIONARYARRAYINTERVIEWQUESTIONSCONCEPTOFSTACKSYSTEMSTACKANDMETHODCALLSRECURSIVEFUNCTIONEXERCISESCHAPTER2:ALGORITHMSANALYSISINTRODUCTIONALGORITHMASYMPTOTICANALYSISBIG-ONOTATIONOMEGA-QNOTATIONTHETA-⊙NOTATIONCOMPLEXITYANALYSISOFALGORITHMSTIMECOMPLEXITYORDERDERIVINGTHERUNTIMEFUNCTIONOFANALGORITHMTIMECOMPLEXITYEXAMPLESMASTERTHEOREMMODIFIEDMASTERTHEOREMEXERCISECHAPTER3:APPROACHTOSOLVEALGORITHMDESIGNPROBLEMSINTRODUCTIONCONSTRAINTSIDEAGENERATIONCOMPLEXITIESCODINGTESTINGEⅹAMPLESUMMARYChaPTER4:ABSTRACTDATATYPEGOCollECtIonsABSTRACTDATATYPE(ADTDATA-STRUCTUREGOCOLLECTIONFRAMEWORKACKQUEUETREEBINARYTREEBINARYSEARCHTREES(BSTPRIORITYQUEUE(HEAPHASH-TABLEDICTIONARY/SYMBOLTABLEGRAPHSGRAPHALGORITHMSSORTINGALGORITHMSCOUNTINGSORTENDNOTEchaPTER5:SEARCHINGINTRODUCTIONWHYSEARCHING?DIFFERENTSEARCHINGALGORITHMSLINEARSEARCH-UNSORTEDINPUTLINEARSEARCH-SORTEDBINARYSEARCHSTRINGSEARCHINGALGORITHMSHASHINGANDSYMBOLTABLESHOWSORTINGISUSEFULINSELECTIONALGORITHM?PROBLEMSINSEARCHINGEXERCISECHAPTER6:SORTINGINTRODUCTIONTYPEOFSORTINGBUBBLE-SORTMODIFIED(IMPROVED)BUBBLE-SORTINSERTION-SORTSELECTION-SORTMERGE-SORTQUICK-SORTQUICKSELECTBUCKETSORTGENERALIZEDBUCKETSORTHEAP-SORTTREESORTINGEXTERNALSORT(EXTERNALMERGE-SORTICOMPARISONSOFTHEVARIOUSSORTINGALGORITHMSSELECTIONOFBESTSORTINGALGORITHMEXERCISEChAPTER7:LINKEDLISTINTRODUCTIONLINKEDLISTTYPESOFLINKEDLISTSINGLYLINKEDLISTDOUBLYLINKEDLISTCIRCULARLINKEDLISTDOUBLYCIRCULARLISTEXERCISEchapter8:STACKINTRODUCTIONTHESTACKABSTRACTDATATYPESTACKUSINGSLICESSTACKGENERICIMPLEMENTATIONSTACKUSINGLINKEDLISTPROBLEMSINSTACKUSESOFSTACKEXERCISEchaPTER9:QUEUEINTRODUCTIONTHEQUEUEABSTRACTDATATYPEQUEUEUSINGLISTQUEUEUSINGLINKEDLISTPROBLEMSINQUEUEEXERCISECHAPTER10:TREEINTRODUCTIONTERMINOLOGYINTREEBINARYTREETYPESOFBINARYTREESPROBLEMSINBINARYTREEBINARYSEARCHTREE(BST)PROBLEMSINBINARYSEARCHTREE(BSTISEGMENTTREEAVLTREESRED-BLACKTREESPLAYTREEB-TREEB+TREEB*TREEEXERCISECHAPTERIl:PRIORITYQUEUEINTRODUCTIONTYPESOFHEAPHEAPADTOPERATIONSOPERATIONONHEAPHEAP-SORTUSESOFHEAPPROBLEMSINHEAPPRIORITYQUEUEGENERICIMPLEMENTATION.PRIORITYQUEUEUSINGHEAPFROMCONTAINER.EXERCISECHAPTER12:HASH-TABLEINTRODUCTIONHASH-TABLEHASHIINGWITHOPENADDRESSINGHASHINGWITHSEPARATECHAININGPROBLEMSINHASHINGEXERCISEChaPTER13:GRAPHSINTRODUCTIONGRAPHREPRESENTATIONADJACENCYMATRIXADJACENCYLISTGRAPHTRAVERSALSDEPTHFIRSTTRAVERSALBREADTHFIRSTTRAVERSALPROBLEMSINGRAPHDIRECTEDACYCLICGRAPHTOPOLOGICALSORTMINIMUMSPANNINGTREES(MST)SHORTESTPATHALGORITHMSINGRAPHEXERCISEChAPTER14:STRINGALGORITHMSTRODUCTIONSTRINGMATCHINGDICTIONARY/SYMBOLTABLEPROBLEMSINSTRINGEXERCISECHAPTER15:ALGORITHMDESIGNTECHNIQUESNTRODUCTIONBRUTEFORCEALGORITHMGREEDYALGORITHMDIVIDE-AND-CONQUER,DECREASE-AND-CONQUERDYNAMICPROGRAMMINGREDUCTIONTRANSFORM-AND-CONQUERBACKTRACKINGBRANCH-AND-BOUNDAALGORITHMCONCLUSIONCHAPTER16:BRUTEFORCEALGORITHMINTRODUCTIONPROBLEMSINBRUTEFORCEALGORITHMCONCLUSIONCHAPTER17:GREEDYALGORITHMINTRODUCTIONPROBLEMSONGREEDYALGORITHMCHAPTER18:DIVIDE-AND-CONQUER,DECREASE-AND-CONQUER

这是A.P.Stokseth的文章："Propertiesofadefocusedopticalsystem"的MATLAB完成。

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。