Deeplearning(DL)hasevolvedinrecentyearswithdevelopmentssuchasgenerativeadversarialnetworks(GANs),variationalautoencoders(VAEs),anddeepreinforcementlearning.ThisbookwillgetyouupandrunningwithR3.5.xtohelpyouimplementDLtechniques.ThebookstartswiththevariousDLtechniquesthatyoucanimplementinyourapps.Auniquesetofrecipeswillhelpyousolvebinomialandmultinomialclassificationproblems,andperformregressionandhyperparameteroptimization.Tohelpyougainhands-onexperienceofconcepts,thebookfeaturesrecipesforimplementingconvolutionalneuralnetworks(CNNs),recurrentneuralnetworks(RNNs),andLongshort-termmemory(LSTMs)networks,aswellassequence-to-sequencemodelsandreinforcementlearning.You’llthenlearnabouthigh-performancecomputationusingGPUs,alongwithlearningaboutparallelcomputationcapabilitiesinR.Later,you’llexplorelibraries,suchasMXNet,thataredesignedforGPUcomputingandstate-of-the-artDL.Finally,you’lldiscoverhowtosolvedifferentproblemsinNLP,objectdetection,andactionidentification,beforeunderstandinghowtousepre-trainedmodelsinDLapps.Bytheendofthisbook,you’llhavecomprehensiveknowledgeofDLandDLpackages,andbeabletodevelopeffectivesolutionsfordifferentDLproblems.