PDF Sudharsan Ravichandiran º Hands On Reinforcement Learning with Python Master º

PDF Sudharsan Ravichandiran º Hands On Reinforcement Learning with Python Master º

★ [PDF / Epub] ☄ Hands On Reinforcement Learning with Python Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow By Sudharsan Ravichandiran ✪ – Ant-web.co A hands on guide enriched with examples to master deep reinforcement learning algorithms with PythonKey FeaturesEnter the world of artificial intelligence using the power of PythonAn example rich guidA hands on guide enriched with examples to master deep reinforcement learning algorithms with PythonKey FeaturesEnter 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 AI Hands On Reinforcement Learning with Python will help you master not only basic reinforcement learning algorithms but also advanced deep reinforcement learning DRL 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 DN DRN A3C PPO and TRPO You will also learn about imagination augmented agents learning from human preference DfD HER and manyof the recent advancements in reinforcement learningBy the end of this 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 RL methods algorithms and elementsTrain an agent to walk using OpenAI Gym and TensorflowUnderstand Markov decision process Bellman's optimality and temporal difference TD learningSolve multi armed bandit problems using various algorithmsMaster deep learning algorithms such as RNN LSTM and CNN with applicationsBuild intelligent agents using the DRN 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 DNWho This Book Is ForHands On Reinforcement Learning with Python is for machine learning developers and deep learning enthusiasts interested in artificial intelligence and want to learn about reinforcement learning from scratch Some knowledge of linear algebra calculus and the Python programming language will help you understand the concepts covered in this bookTable 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 RecurrentNetworkAsynchronous Advantage Actor Critic NetworkPolicy Gradients and OptimizationCapstone Project Car Racing using DN.

hands mobile reinforcement epub learning mobile with mobile python book master download reinforcement book deep download reinforcement free learning free using pdf openai pdf tensorflow free Hands On pdf Reinforcement Learning free Reinforcement Learning with Python pdf On Reinforcement Learning mobile On Reinforcement Learning with Python epub Hands On Reinforcement Learning with Python Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow KindleA hands on guide enriched with examples to master deep reinforcement learning algorithms with PythonKey FeaturesEnter 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 AI Hands On Reinforcement Learning with Python will help you master not only basic reinforcement learning algorithms but also advanced deep reinforcement learning DRL 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 DN DRN A3C PPO and TRPO You will also learn about imagination augmented agents learning from human preference DfD HER and manyof the recent advancements in reinforcement learningBy the end of this 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 RL methods algorithms and elementsTrain an agent to walk using OpenAI Gym and TensorflowUnderstand Markov decision process Bellman's optimality and temporal difference TD learningSolve multi armed bandit problems using various algorithmsMaster deep learning algorithms such as RNN LSTM and CNN with applicationsBuild intelligent agents using the DRN 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 DNWho This Book Is ForHands On Reinforcement Learning with Python is for machine learning developers and deep learning enthusiasts interested in artificial intelligence and want to learn about reinforcement learning from scratch Some knowledge of linear algebra calculus and the Python programming language will help you understand the concepts covered in this bookTable 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 RecurrentNetworkAsynchronous Advantage Actor Critic NetworkPolicy Gradients and OptimizationCapstone Project Car Racing using DN.


A hands on guide enriched with examples to master deep reinforcement learning algorithms with PythonKey FeaturesEnter 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 AI Hands On Reinforcement Learning with Python will help you master not only basic reinforcement learning algorithms but also advanced deep reinforcement learning DRL 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 DN DRN A3C PPO and TRPO You will also learn about imagination augmented agents learning from human preference DfD HER and manyof the recent advancements in reinforcement learningBy the end of this 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 RL methods algorithms and elementsTrain an agent to walk using OpenAI Gym and TensorflowUnderstand Markov decision process Bellman's optimality and temporal difference TD learningSolve multi armed bandit problems using various algorithmsMaster deep learning algorithms such as RNN LSTM and CNN with applicationsBuild intelligent agents using the DRN 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 DNWho This Book Is ForHands On Reinforcement Learning with Python is for machine learning developers and deep learning enthusiasts interested in artificial intelligence and want to learn about reinforcement learning from scratch Some knowledge of linear algebra calculus and the Python programming language will help you understand the concepts covered in this bookTable 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 RecurrentNetworkAsynchronous Advantage Actor Critic NetworkPolicy Gradients and OptimizationCapstone Project Car Racing using DN.

PDF Sudharsan Ravichandiran º Hands On Reinforcement Learning with Python Master º

PDF Sudharsan Ravichandiran º Hands On Reinforcement Learning with Python Master º

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