ReinforcementlearninghasevolvedalotinthelastcoupleofyearsandproventobeasuccessfultechniqueinbuildingsmartandintelligentAInetworks.KerasReinforcementLearningProjectsinstallshuman-levelperformanceintoyourapplicationsusingalgorithmsandtechniquesofreinforcementlearning,coupledwithKeras,afasterexperimentallibrary.ThebookbeginswithgettingyouupandrunningwiththeconceptsofreinforcementlearningusingKeras.You’lllearnhowtosimulatearandomwalkusingMarkovchainsandselectthebestportfoliousingdynamicprogramming(DP)andPython.You’llalsoexploreprojectssuchasforecastingstockpricesusingMonteCarlomethods,deliveringvehicleroutingapplicationusingTemporalDistance(TD)learningalgorithms,andbalancingaRotatingMechanicalSystemusingMarkovdecisionprocesses.Onceyou’veunderstoodthebasics,you’llmoveontoModelingofaSegway,runningarobotcontrolsystemusingdeepreinforcementlearning,andbuildingahandwrittendigitrecognitionmodelinPythonusinganimagedataset.Finally,you’llexcelinplayingtheboardgameGowiththehelpofQ-Learningandreinforcementlearningalgorithms.Bytheendofthisbook,you’llnotonlyhavedevelopedhands-ontrainingonconcepts,algorithms,andtechniquesofreinforcementlearningbutalsobeallsettoexploretheworldofAI.