Reinforcementlearningisoneofthemostexcitingandrapidlygrowingfieldsinmachinelearning.Thisisduetothemanynovelalgorithmsdevelopedandincredibleresultspublishedinrecentyears.Inthisbook,youwilllearnaboutthecoreconceptsofRLincludingQ-learning,policygradients,MonteCarloprocesses,andseveraldeepreinforcementlearningalgorithms.Asyoumakeyourwaythroughthebook,you'llworkonprojectswithdatasetsofvariousmodalitiesincludingimage,text,andvideo.Youwillgainexperienceinseveraldomains,includinggaming,imageprocessing,andphysicalsimulations.You'llexploretechnologiessuchasTensorFlowandOpenAIGymtoimplementdeeplearningreinforcementlearningalgorithmsthatalsopredictstockprices,generatenaturallanguage,andevenbuildotherneuralnetworks.Bytheendofthisbook,youwillhavehands-onexperiencewitheightreinforcementlearningprojects,eachaddressingdifferenttopicsand/oralgorithms.Wehopethesepracticalexerciseswillprovideyouwithbetterintuitionandinsightaboutthefieldofreinforcementlearningandhowtoapplyitsalgorithmstovariousproblemsinreallife.