Developersstruggletofindaneasy-to-followlearningresourceforimplementingRecurrentNeuralNetwork(RNN)models.RNNsarethestate-of-the-artmodelindeeplearningfordealingwithsequentialdata.Fromlanguagetranslationtogeneratingcaptionsforanimage,RNNsareusedtocontinuouslyimproveresults.ThisbookwillteachyouthefundamentalsofRNNs,withexampleapplicationsinPythonandtheTensorFlowlibrary.Theexamplesareaccompaniedbytherightcombinationoftheoreticalknowledgeandreal-worldimplementationsofconceptstobuildasolidfoundationofneuralnetworkmodeling.YourjourneystartswiththesimplestRNNmodel,whereyoucangraspthefundamentals.Thebookthenbuildsonthisbyproposingmoreadvancedandcomplexalgorithms.Weusethemtoexplainhowatypicalstate-of-the-artRNNmodelworks.Fromgeneratingtexttobuildingalanguagetranslator,weshowhowsomeoftoday'smostpowerfulAIapplicationsworkunderthehood.Afterreadingthebook,youwillbeconfidentwiththefundamentalsofRNNs,andbereadytopursuefurtherstudy,alongwithdevelopingskillsinthisexcitingfield.