Withhugeamountsofdatabeinggeneratedeverymoment,businessesneedapplicationsthatapplycomplexmathematicalcalculationstodatarepeatedlyandatspeed.WithmachinelearningtechniquesandR,youcaneasilydevelopthesekindsofapplicationsinanefficientway.PracticalMachineLearningwithRbeginsbyhelpingyougraspthebasicsofmachinelearningmethods,whilealsohighlightinghowandwhytheywork.Youwillunderstandhowtogetthesealgorithmstoworkinpractice,ratherthanfocusingonmathematicalderivations.Asyouprogressfromonechaptertoanother,youwillgainhands-onexperienceofbuildingamachinelearningsolutioninR.Next,usingRpackagessuchasrpart,randomforest,andmultipleimputationbychainedequations(MICE),youwilllearntoimplementalgorithmsincludingneuralnetclassifier,decisiontrees,andlinearandnon-linearregression.Asyouprogressthroughthebook,you’lldelveintovariousmachinelearningtechniquesforbothsupervisedandunsupervisedlearningapproaches.Inadditiontothis,you’llgaininsightsintopartitioningthedatasetsandmechanismstoevaluatetheresultsfromeachmodelandbeabletocomparethem.Bytheendofthisbook,youwillhavegainedexpertiseinsolvingyourbusinessproblems,startingbyformingagoodproblemstatement,selectingthemostappropriatemodeltosolveyourproblem,andthenensuringthatyoudonotovertrainit.