RoseVMCluster(Mirror)forWindows维护手册v2.2.pdf

RodriguezA,LaioA.Clusteringbyfastsearchandfindofdensitypeaks[J].Science,2014,344(6191):1492-1496.基于这篇文章实现的最基本的密度聚类的算法，具体请看我博客中的相关文章http://blog.csdn.net/kryolith/article/details/39832573

DeriveusefulinsightsfromyourdatausingPython.Learnthetechniquesrelatedtonaturallanguageprocessingandtextanalytics,andgaintheskillstoknowwhichtechniqueisbestsuitedtosolveaparticularproblem.TextAnalyticswithPythonteachesyoubothbasicandadvancedconcepts,includingtextandlanguagesyntax,structure,semantics.Youwillfocusonalgorithmsandtechniques,suchastextclassification,clustering,topicmodeling,andtextsummarization.Astructuredandcomprehensiveapproachisfollowedinthisbooksothatreaderswithlittleornoexperiencedonotfindthemselvesoverwhelmed.YouwillstartwiththebasicsofnaturallanguageandPythonandmoveontoadvancedanalyticalandmachinelearningconcepts.Youwilllookateachtechniqueandalgorithmwithbothabird'seyeviewtounderstandhowitcanbeusedaswellaswithamicroscopicviewtounderstandthemathematicalconceptsandtoimplementthemtosolveyourownproblems.ThisbookProvidescompletecoverageofthemajorconceptsandtechniquesofnaturallanguageprocessing(NLP)andtextanalyticsIncludespracticalreal-worldexamplesoftechniquesforimplementation,suchasbuildingatextclassificationsystemtocategorizenewsarticles,analyzingapporgamereviewsusingtopicmodelingandtextsummarization,andclusteringpopularmoviesynopsesandanalyzingthesentimentofmoviereviewsShowsimplementationsbasedonPythonandseveralpopularopensourcelibrariesinNLPandtextanalytics,suchasthenaturallanguagetoolkit(nltk),gensim,scikit-learn,spaCyandPatternWhatyouwilllearnNaturalLanguageconceptsAnalyzingTextsyntaxandstructureTextClassificationTextClusteringandSimilarityanalysisTextSummarizationSemanticandSentimentanalysisReadershipThebookisforITprofessionals,analysts,developers,linguisticexperts,datascientists,andanyonewithakeeninterestinlinguistics,analytics,andgeneratinginsightsfrom

FastSubspaceClusteringviaSparseRepresentations利用系数表示做快速子空间聚类matlabd代码优于SSC

来自于GOOGLE的mapreduce的开山之作，此文是原英文的中文版本，希望能互相参照，加深理解

FEniCSisapopularopen-source(LGPLv3)computingplatformforsolvingpartialdifferentialequations(PDEs).FEniCSenablesuserstoquicklytranslatescientificmodelsintoefficientfiniteelementcode.Withthehigh-levelPythonandC++interfacestoFEniCS,itiseasytogetstarted,butFEniCSoffersalsopowerfulcapabilitiesformoreexperiencedprogrammers.FEniCSrunsonamultitudeofplatformsrangingfromlaptopstohigh-performanceclusters.

redis的python客户端，需要使用redis3.0以上的cluster需要先安装redis，再安装rediscluster.py

KeyFeaturesLeverageCeph'sadvancedfeaturessuchaserasurecoding,tiering,andBluestoreSolvelarge-scaleproblemswithCephasatoolbyunderstandingitsstrengthsandweaknessestodevelopthebestsolutionsApracticalguidethatcoversengagingusecasestohelpyouuseadvancedfeaturesofCepheffectivelyBookDescriptionMasteringCephcoversallthatyouneedtoknowtouseCepheffectively.Startingwithdesigngoalsandplanningstepsthatshouldbeundertakentoensuresuccessfuldeployments,youwillbeguidedthroughtosettingupanddeployingtheCephcluster,withthehelpoforchestrationtools.KeyareasofCephincludingBluestore,Erasurecodingandcachetieringwillbecoveredwithhelpofexamples.DevelopmentofapplicationswhichuseLibradosandDistributedcomputationswithsharedobjectclassesarealsocovered.AsectionontuningwilltakeyouthroughtheprocessofoptimisizingbothCephanditssupportinginfrastructure.Finally,youwilllearntotroubleshootissuesandhandlevariousscenarioswhereCephislikelynottorecoveronitsown.Bytheendofthebook,youwillbeabletosuccessfullydeployandoperatearesilienthighperformanceCephcluster.WhatyouwilllearnKnowwhenandhowtousesomeofCeph'sadvancednewfeaturesSetupatestclusterwithAnsibleandsomevirtualmachinesusingVirtualBoxandVagrantDevelopnovelsolutionstomassiveproblemswithlibradosandsharedobjectclasses.Chooseintelligentparametersforanerasurecodedpoolandsetitup.ConfiguretheBluestoresettingsandseehowtheyinteractwithdifferenthardwareconfigurations.KeepCephrunningthroughthickandthinwithtuning,monitoringanddisasterrecoveryadvice.AbouttheAuthorNickFiskisanITspecialistwithastronghistoryinenterprisestorage.Havingworkedinavarietyofrolesthroughouthiscareer,hehasencounteredawidevarietyoftechnologies.In2012,Nickwasgiventheopportunitytofocusmoretow

最近学习springboot吧自己工作中需要用到的工具都做了集成例子。
其中包括mybatis，cfx的webservice，定时器quartz，消息队列kafka以及redis其中redis包含了三种连接方式（单机模式，集群cluster，哨兵模式），给大家做一个参考希望能让别人学习时少走弯路

Thispaperproposesanewmethodtoweightsubspacesinfeaturegroupsandindividualfeaturesforclusteringhigh-dimensionaldata.Inthismethod,thefeaturesofhigh-dimensionaldataaredividedintofeaturegroups,basedontheirnaturalcharacteristics.Twotypesofweightsareintroducedtotheclusteringprocesstosimultaneouslyidentifytheimportanceoffeaturegroupsandindividualfeaturesineachcluster.Anewoptimizationmodelisgiventodefinetheoptimizationprocessandane

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。