Statistical-Learning-Method_Codedemo

Henry-Liang's-FRM-Guide-II-for-Case-Learning，次要用于FRM考试案列分享，内容很精美，分享给大家，次要用于学习研究目的哈，希望大家考研考出好成绩，考出风格和水平

PracticalStatisticsforDataScientists50EssentialConcepts英文无水印转化版pdfpdf一切页面使用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PracticalstatisticsfordatascientistsbypeterbruceandandrewbruceCopyright@2017PeterBruceandAndrewBruce.AllrightsreservedPrintedintheunitedstatesofamericaPublishedbyo'reillymedia,InC.1005GravensteinHighwayNorth,Sebastopol,Ca95472O'Reillybooksmaybepurchasedforeducational,business,orsalespromotionaluse.onlineeditionsarealsoavailableformosttitles(http:/oreilly.com/safari)Formoreinformation,contactourcorporate/institutionalsalesdepartment:800998-9938orcorporateoreillycom■editor:ShannoncuttProductioneditor.KristenbrownCopyeditor:RachelmonaghanaProofreadereliahusussmanaIndexerEllenTroutman-ZaigaInteriorDesigner:DavidFutatoCoverDesigner:KarenMontgomeryllustrator.rebeccademarestaMay2017:FirstEditionRevisionhistoryfortheFirstedition2017-05-09FirstreleaseSeehttp://oreilly.com/catalog/errata.csp?isbn=9781491952962forreleasedetailsTheoreillylogoisaregisteredtrademarkofo'reillymedia,Inc.PracticalStatisticsforDataScientists,thecoverimage,andrelatedtradedressaretrademarksofo'ReillyMedia,IncWhilethepublisherandtheauthorshaveusedgoodfaitheffortstoensurethattheinformationandinstructionscontainedinthisworkareaccurate,thepublisherandtheauthorsdisclaimallresponsibilityforerrorsoromissions,includingwithoutlimitationresponsibilityfordamagesresultingfromtheuseoforrelianceonthiswork.Useoftheinformationandinstructionscontainedinthisworkisatyourownrisk.Ifanycodesamplesorothertechnologythisworkcontainsordescribesissubjecttoopensourcelicensesortheintellectualpropertyrightsofothers,itisyourresponsibilitytoensurethatyourusethereofcomplieswithsuchlicensesand/orrights978-1-491-95296-2DedicationWewouldliketodedicatethisbooktothememoriesofourparentsVictorgBruceandNancyC.bruce,whocultivatedapassionformathandscienceandtoourearlymentorsJohnW.TukeyandJulianSimon,andourlifelongfriendGeoffWatson,whohelpedinspireustopursueacareerinstatisticsPrefaceThisbookisaimedatthedatascientistwithsomefamiliaritywiththerprogramminglanguage,andwithsomeprior(perhapsspottyorephemeral)exposuretostatistics.Bothofuscametotheworldofdatasciencefromtheworldofstatistics,sowehavesomeappreciationofthecontributionthatstatisticscanmaketotheartofdatascience.atthesametimewearewellawareofthelimitationsoftraditionalstatisticsinstruction:statisticsasadisciplineisacenturyandahalfoldandmoststatisticstextbooksandcoursesareladenwiththemomentumandinertiaofanoceanlinerTwogoalsunderliethisbookTolayout,indigestible,navigable,andeasilyreferencedform,keyconceptsfromstatisticsthatarerelevanttodatascienceToexplainwhichconceptsareimportantandusefulfromadatascienceperspective,whicharelessso,andwhyWhattoExpectKEYTERMSDatascienceisafusionofmultipledisciplines,inchidingstatistics,computerscience,informationtechnology,anddomain-specificfields.Asaresult,severaldifferenttermscouldbeusedtoreferenceaivenconcept.KeytermsandtheirsynonymswillbehighlightedthroughoutthebooknasidebarsuchasConventionsusedinThisbookThefollowingtypographicalconventionsareusedinthisbookItalicIndicatesnewtermsURls.emailaddressesfilenamesandfileextensionsConstantwidthUsedforprogramlistings,aswellaswithinparagraphstorefertoprogramelementssuchasvariableorfunctionnames,databases,datatypes,environmentvariables,statements,andkeywordsConstantwidthboldShowscommandsorothertextthatshouldbetypedliterallybytheuserConstantwidthitalicShowstextthatshouldbereplacedwithuser-suppliedvaluesorbyvaluesdeterminedbycontextTIPThiselementsignifiesatiporsuggestionNOTEThiselementsignifiesageneralnoteWARNINGThiselementindicatesawarningorcautionUsingCodeExamplesSupplementalmaterial(codeexamples,exercises,etc.isavailablefordownloadathttps://github.com/andrewgbruce/statistics-for-data-scientistsThisbookisheretohelpyougetyourjobdone.Ingeneral,ifexamplecodeisofferedwiththisbook,youmayuseitinyourprogramsanddocumentation.youdonotneedtocontactusforpermissionunlessyou'rereproducingasignificantportionofthecode.Forexample,writingaprogramthatusesseveralchunksofcodefromthisbookdoesnotrequirepermission.SellingordistributingaCD-ROMofexamplesfromOReillybooksdoesrequirepermission.answeringaquestionbycitingthisbookandquotingexamplecodedoesnotrequirepermission.Incorporatingasignificantamountofexamplecodefromthisbookintoyourproduct'sdocumentationdoesrequirepermissionWeappreciate,butdonotrequire,attribution.Anattributionusuallyincludesthetitle,author,publisher,andisBN.Forexample:PracticalStatisticsfordataScientistsbyPeterBruceandAndrewBruce(o'Reilly).Copyright2017PeterBruceandandrewbruce.978-1-491-95296-2Ifyoufeelyouruseofcodeexamplesfallsoutsidefairuseorthepermissiongivenabove,feelfreetocontactusatpermissions(@oreilly.comSafari(BooksonlineNOTESafaribooksOnlineisanon-demanddigitallibrarythatdeliversexpertcontentinbothbookandvideoformfromtheworldsleadingauthorsintechnologyandbusinessTechnologyprofessionals,softwaredevelopers,webdesigners,andbusinessandcreativeprofessionalsuseSafariBooksOnlineastheirprimaryr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强化学习中的一个重要里程碑就是Q学习算法，使用matlab进行单步Q学习无妨碍路径规划仿真，设学习次数为200.

神经网络与机器学习在matlab中完成英文原版书中含有代码指的参考

Informationtheoryandinference,taughttogetherinthisexcitingtextbook,lieattheheartofmanyimportantareasofmoderntechnology-co妹妹unication,signalprocessing,datamining,machinelearning,patternrecognition,computationalneuroscience,bioinformaticsandcryptography.Thebookintroducestheoryintandemwithapplications.Informationtheoryistaughtalongsidepracticalco妹妹unicationsystemssuchasarithmeticcodingfordatacompressionandsparse-graphcodesforerror-correction.Inferencetechniques,includingmessage-passingalgorithms,MonteCarlomethodsandvariationalapproximations,aredevelopedalongsideapplicationstoclustering,convolutionalcodes,independentcomponentanalysis,andneuralnetworks.Uniquely,thebookcoversstate-of-the-arterror-correctingcodes,includinglow-density-parity-checkcodes,turbocodes,anddigitalfountaincodes-thetwenty-first-centurystandardsforsatelliteco妹妹unications,diskdrives,anddatabroadcast.Richlyillustrated,filledwithworkedexamplesandover400exercises,somewithdetailedsolutions,thebookisidealforself-learning,andforundergraduateorgraduatecourses.Italsoprovidesanunparalleledentrypointforprofessionalsinareasasdiverseascomputationalbiology,financialengineeringandmachinelearning.

Q-learning是一种模型有关的强化学习方法，本文档使用Q-learning做了一个简单的搜索任务，有助于初学者理解强化学习，理解Q-learning.

master_machine_learning_algorithms

这个是我认为最好的机器学习的入门材料了，我还把书里面每个仿真都跑了，因为在git上下载的程序有些问题。
我都改好了。

https://github.com/fchollet/deep-learning-models/releases/tag/v0.1这网址下的keras的一切的预训练模型，包含vgg16,vgg19,resnt50,官方下载实在是太慢了。
我这里提供了百度云链接，注册一天的百度云会员下载会很快的。

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。