Î Hands-On Reinforcement Learning with Python: Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow (English Edition) ✓ Download by Î Sudharsan Ravichandiran
Î Hands-On Reinforcement Learning with Python: Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow (English Edition) ✓ Download by Î Sudharsan Ravichandiran reinforcement learning made simple Simple solid math when needed, with good python code. Solid introduction to reinforcement learning traditional strategies and modern deep reinforcement learning. Definitively recommend. I have not gone through all the chapters yet but this looks promising for detailed knowledge Great to have this book.
Clear description and implementation on those RL algorithm But this book cannot tell you why it works No proof or comparison on different algorithm. A Hands On Guide Enriched With Examples To Master Deep Reinforcement Learning Algorithms With PythonKey FeaturesYour Entry Point Into The World Of Artificial Intelligence Using The Power Of PythonAn Example Rich Guide To Master Various RL And DRL AlgorithmsExplore Various State Of The Art Architectures Along With MathBook DescriptionReinforcement Learning RL Is The Trending And Most Promising Branch Of Artificial Intelligence Hands On Reinforcement Learning With Python Will Help You Master Not Only The Basic Reinforcement Learning Algorithms But Also The Advanced Deep Reinforcement Learning AlgorithmsThe Book Starts With An Introduction To Reinforcement Learning Followed By OpenAI Gym, And TensorFlow You Will Then Explore Various RL Algorithms And Concepts, Such As Markov Decision Process, Monte Carlo Methods, And Dynamic Programming, Including Value And Policy Iteration This Example Rich Guide Will Introduce You To Deep Reinforcement Learning Algorithms, Such As Dueling DQN, DRQN, AC, PPO, And TRPO You Will Also Learn About Imagination Augmented Agents, Learning From Human Preference, DQfD, HER, And Many Of The Recent Advancements In Reinforcement LearningBy The End Of The Book, You Will Have All The Knowledge And Experience Needed To Implement Reinforcement Learning And Deep Reinforcement Learning In Your Projects, And You Will Be All Set To Enter The World Of Artificial IntelligenceWhat You Will LearnUnderstand The Basics Of Reinforcement Learning Methods, Algorithms, And ElementsTrain An Agent To Walk Using OpenAI Gym And TensorflowUnderstand The Markov Decision Process, Bellmans Optimality, And TD LearningSolve Multi Armed Bandit Problems Using Various AlgorithmsMaster Deep Learning Algorithms, Such As RNN, LSTM, And CNN With ApplicationsBuild Intelligent Agents Using The DRQN Algorithm To Play The Doom GameTeach Agents To Play The Lunar Lander Game Using DDPGTrain An Agent To Win A Car Racing Game Using Dueling DQNWho This Book Is ForIf Youre A Machine Learning Developer Or Deep Learning Enthusiast Interested In Artificial Intelligence And Want To Learn About Reinforcement Learning From Scratch, This Book Is For You Some Knowledge Of Linear Algebra, Calculus, And The Python Programming Language Will Help You Understand The Concepts Covered In This Book Table Of ContentsIntroduction To Reinforcement LearningGetting Started With OpenAI And TensorflowMarkov Decision Process And Dynamic ProgrammingGaming With Monte Carlo Tree SearchTemporal Difference LearningMulti Armed Bandit ProblemDeep Learning FundamentalsDeep Learning And ReinforcementPlaying Doom With Deep Recurrent Q NetworkAsynchronous Advantage Actor Critic NetworkPolicy Gradients And OptimizationCapstone Project Car Racing Using DQNCurrent Research And Next StepsSudharsan Ravichandiran Is A Data Scientist, Researcher, Artificial Intelligence Enthusiast, And YouTuber Search For Sudharsan Reinforcement Learning He Completed His Bachelors In Information Technology At Anna University His Area Of Research Focuses On Practical Implementations Of Deep Learning And Reinforcement Learning, Which Includes Natural Language Processing And Computer Vision He Used To Be A Freelance Web Developer And Designer And Has Designed Award Winning Websites He Is An Open Source Contributor And Loves Answering Questions On Stack Overflow