2017全球虚拟货币关键数据调查Thisisthefirststudytosystematicallyinvestigatekeycryptocurrencyindustrysectorsbycollectingempirical,non-publicdata.Thestudygatheredsurveydatafromnearly150cryptocurrencycompaniesandindividuals,anditcovers38countriesfromfiveworldregions.Thestudydetailsthekeyindustrysectorsthathaveemergedandthedifferententitiesthatinhabitthem.

NonlinearModelPredictiveControl_TheoryandAlgorithms：secondedition

NTLisaportableC++libraryprovidingtoolsfor:ArbitraryintegerandfloatingpointarithmeticPolynomialArithmeticLatticebasisreductionBasiclinearalgebra

DLT全称DirectLinearTransformation这个资源是Matlab版本获取相机参数(C/C++版本的也实现了但是没有在这个资源里,想要的童鞋可以联系我)

GloVeisanunsupervisedlearningalgorithmforobtainingvectorrepresentationsforwords.Trainingisperformedonaggregatedglobalword-wordco-occurrencestatisticsfromacorpus,andtheresultingrepresentationsshowcaseinterestinglinearsubstructuresofthewordvectorspace.

High-PerformanceLinear/InterfaceABT,ABTE,AHC,ALVT,BTL,CAN(ISO-11898),CDC,CompactPCI,FB+,Firewire,FlatLink,GigabitEthernet/10GEthernet,GTL,GTLP,HSTL,IEEE1284,IEEE1394,LVDM,LVDS,LVT,M-LVDS,PCI,TIA/EIA-232,RS-232,TIA/EIA-422,RS-422,TIA/EIA-485,RS-485,TIA/EIA-644,T

美国各大高校的教材的参考资料，仅供参考，为了帮助更多的人。

AnEnsembleKalmanSmootherforNonlinearDynamics.pdf

Thispracticalguideprovidesnearly200self-containedrecipestohelpyousolvemachinelearningchallengesyoumayencounterinyourdailywork.Ifyou’recomfortablewithPythonanditslibraries,includingpandasandscikit-learn,you’llbeabletoaddressspecificproblemssuchasloadingdata,handlingtextornumericaldata,modelselection,anddimensionalityreductionandmanyothertopics.Eachrecipeincludescodethatyoucancopyandpasteintoatoydatasettoensurethatitactuallyworks.Fromthere,youcaninsert,combine,oradaptthecodetohelpconstructyourapplication.Recipesalsoincludeadiscussionthatexplainsthesolutionandprovidesmeaningfulcontext.Thiscookbooktakesyoubeyondtheoryandconceptsbyprovidingthenutsandboltsyouneedtoconstructworkingmachinelearningapplications.You’llfindrecipesfor:Vectors,matrices,andarraysHandlingnumericalandcategoricaldata,text,images,anddatesandtimesDimensionalityreductionusingfeatureextractionorfeatureselectionModelevaluationandselectionLinearandlogicalregression,treesandforests,andk-nearestneighborsSupportvectormachines(SVM),naïveBayes,clustering,andneuralnetworksSavingandloadingtrainedmodels

LinearSystemsThomasKailath加了详细书签英文扫描版

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。