Deeplearningisapowerfulsubsetofmachinelearningthatisverysuccessfulindomainssuchascomputervisionandnaturallanguageprocessing(NLP).ThissecondeditionofRDeepLearningEssentialswillopenthegatesforyoutoentertheworldofneuralnetworksbybuildingpowerfuldeeplearningmodelsusingtheRecosystem.Thisbookwillintroduceyoutothebasicprinciplesofdeeplearningandteachyoutobuildaneuralnetworkmodelfromscratch.Asyoumakeyourwaythroughthebook,youwillexploredeeplearninglibraries,suchasKeras,MXNet,andTensorFlow,andcreateinterestingdeeplearningmodelsforavarietyoftasksandproblems,includingstructureddata,computervision,textdata,anomalydetection,andrecommendationsystems.You’llcoveradvancedtopics,suchasgenerativeadversarialnetworks(GANs),transferlearning,andlarge-scaledeeplearninginthecloud.Intheconcludingchapters,youwilllearnaboutthetheoreticalconceptsofdeeplearningprojects,suchasmodeloptimization,overfitting,anddataaugmentation,togetherwithotheradvancedtopics.Bytheendofthisbook,youwillbefullypreparedandabletoimplementdeeplearningconceptsinyourresearchworkorprojects.