StructuredStreaming是一个可拓展,容错的,基于SparkSQL执行引擎的流处理引擎。
使用小量的静态数据模拟流处理。
伴随流数据的到来,SparkSQL引擎会逐渐连续处理数据并且更新结果到最终的Table中。
你可以在SparkSQL上引擎上使用DataSet/DataFrameAPI处理流数据的聚集,事件窗口,和流与批次的连接操作等。
最后StructuredStreaming系统快速,稳定,端到端的恰好一次保证,支持容错的处理。
2023/8/6 3:19:22 6.64MB Spark Streaming
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Today,machinelearningunderliesarangeofapplicationsweuseeveryday,fromproductrecommendationstovoicerecognition--aswellassomewedon'tyetuseeveryday,includingdriverlesscars.Itisthebasisofthenewapproachincomputingwherewedonotwriteprogramsbutcollectdata;theideaistolearnthealgorithmsforthetasksautomaticallyfromdata.Ascomputingdevicesgrowmoreubiquitous,alargerpartofourlivesandworkisrecordeddigitally,andas"BigData"hasgottenbigger,thetheoryofmachinelearning--thefoundationofeffortstoprocessthatdataintoknowledge--hasalsoadvanced.Inthisbook,machinelearningexpertEthemAlpaydinoffersaconciseoverviewofthesubjectforthegeneralreader,describingitsevolution,explainingimportantlearningalgorithms,andpresentingexampleapplications.Alpaydinoffersanaccountofhowdigitaltechnologyadvancedfromnumber-crunchingmainframestomobiledevices,puttingtoday'smachinelearningboomincontext.Hedescribesthebasicsofmachinelearningandsomeapplications;theuseofmachinelearningalgorithmsforpatternrecognition;artificialneuralnetworksinspiredbythehumanbrain;algorithmsthatlearnassociationsbetweeninstances,withsuchapplicationsascustomersegmentationandlearningrecommendations;andreinforcementlearning,whenanautonomousagentlearnsactsoastomaximizerewardandminimizepenalty.Alpaydinthenconsiderssomefuturedirectionsformachinelearningandthenewfieldof"datascience,"anddiscussestheethicalandlegalimplicationsfordataprivacyandsecurity.TableofContentsChapter1WhyWeAreInterestedInMachineLearningChapter2MachineLearning,Statistics,AndDataAnalyticsChapter3PatternRecognitionChapter4NeuralNetworksAndDeepLearningChapter5LearningClustersAndRecommendationsChapter6LearningToTakeActionsChapter7WhereDoWeGoFromHere?
2023/7/11 7:13:56 1.82MB Machine Learning New AI
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对深度强化学习的基本操作的程序。
2023/7/10 5:27:28 14.03MB 深度学习
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NeurIPS-2020-no-regret-learning-dynamics-for-extensive-form-correlated-equilibrium-Paper
2023/7/7 22:03:53 1.42MB 机器学习
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WelcomeWelcometoXGBoostWithPython.ThisbookisyourguidetofastgradientboostinginPython.YouwilldiscovertheXGBoostPythonlibraryforgradientboostingandhowtouseittodevelopandevaluategradientboostingmodels.Inthisbookyouwilldiscoverthetechniques,recipesandskillswithXGBoostthatyoucanthenbringtoyourownmachinelearningprojects.GradientBoostingdoeshaveasomefascinatingmathunderthecovers,butyoudonotneedtoknowittobeabletopickitupasatoolandwielditonimportantprojectstodeliverrealvalue.Fromtheappliedperspective,gradientboostingisquiteashallowfieldandamotivateddevelopercanquicklypickitupandstartmakingveryrealandimpactfulcontributions.Thisismygoalforyouandthisbookisyourtickettothatoutcome.
2023/6/14 15:42:44 2.07MB machine lear mastery xgboost
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KeyFeaturesLearnPyTorchforimplementingcutting-edgedeeplearningalgorithms.Trainyourneuralnetworksforhigherspeedandflexibilityandlearnhowtoimplementtheminvariousscenarios;CovervariousadvancedneuralnetworkarchitecturesuchasResNet,Inception,DenseNetandmorewithpracticalexamples;
2023/5/5 22:23:46 7.2MB pytorch
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数据开掘与R语言,案例涵盖了首要的数据开掘本领,给出了齐全的代码。
2023/5/2 0:25:26 2.22MB 数据挖掘 R语言
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Learning-basedVideoMotionMagnification代码
2023/4/22 3:13:04 20KB 运动放大
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Roughlyinspiredbythehumanbrain,deepneuralnetworkstrainedwithlargeamountsofdatacansolvecomplextaskswithunprecedentedaccuracy.Thispracticalbookprovidesanend-to-endguidetoTensorFlow,theleadingopensourcesoftwarelibrarythathelpsyoubuildandtrainneuralnetworksforcomputervision,naturallanguageprocessing(NLP),speechrecognition,andgeneralpredictiveanalytics.AuthorsTomHope,YehezkelResheff,andItayLiederprovideahands-onapproachtoTensorFlowfundamentalsforabroadtechnicalaudience—fromdatascientistsandengineerstostudentsandresearchers.You’llbeginbyworkingthroughsomebasicexamplesinTensorFlowbeforedivingdeeperintotopicssuchasneuralnetworkarchitectures,TensorBoardvisualization,TensorFlowabstractionlibraries,andmultithreadedinputpipelines.Onceyoufinishthisbook,you’llknowhowtobuildanddeployproduction-readydeeplearningsystemsinTensorFlow.
2023/4/18 0:28:20 12.64MB Learning TensorFlow
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Delveintoneuralnetworks,implementdeeplearningalgorithms,andexplorelayersofdataabstractionwiththehelpofthiscomprehensiveTensorFlowguideAboutThisBookLearnhowtoimplementadvancedtechniquesindeeplearningwithGoogle’sbrainchild,TensorFlowExploredeepneuralnetworksa
2023/4/17 16:19:03 6.2MB TensorFlow Deep Learning
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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。
2024-04-09 15:03 15KB 钉钉 钉钉打卡