Ensemblemodelingisanapproachusedtoimprovetheperformanceofmachinelearningmodels.Itcombinestwoormoresimilarordissimilarmachinelearningalgorithmstodeliversuperiorintellectualpowers.Thisbookwillhelpyoutoimplementpopularmachinelearningalgorithmstocoverdifferentparadigmsofensemblemachinelearningsuchasboosting,bagging,andstacking.TheEnsembleMachineLearningCookbookwillstartbygettingyouacquaintedwiththebasicsofensembletechniquesandexploratorydataanalysis.You'llthenlearntoimplementtasksrelatedtostatisticalandmachinelearningalgorithmstounderstandtheensembleofmultipleheterogeneousalgorithms.Itwillalsoensurethatyoudon'tmissoutonkeytopics,suchaslikeresamplingmethods.Asyouprogress,you’llgetabetterunderstandingofbagging,boosting,stacking,andworkingwiththeRandomForestalgorithmusingreal-worldexamples.Thebookwillhighlighthowtheseensemblemethodsusemultiplemodelstoimprovemachinelearningresults,ascomparedtoasinglemodel.Intheconcludingchapters,you'lldelveintoadvancedensemblemodelsusingneuralnetworks,naturallanguageprocessing,andmore.You’llalsobeabletoimplementmodelssuchasfrauddetection,textcategorization,andsentimentanalysis.Bytheendofthisbook,you'llbeabletoharnessensembletechniquesandtheworkingmechanismsofmachinelearningalgorithmstobuildintelligentmodelsusingindividualrecipes.