Deep Reinforcement Learning with Python Book [PDF] Download

Download the fantastic book titled Deep Reinforcement Learning with Python written by Nimish Sanghi, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Deep Reinforcement Learning with Python", which was released on 12 June 2021. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.

Summary of Deep Reinforcement Learning with Python by Nimish Sanghi PDF

Deep reinforcement learning is a fast-growing discipline that is making a significant impact in fields of autonomous vehicles, robotics, healthcare, finance, and many more. This book covers deep reinforcement learning using deep-q learning and policy gradient models with coding exercise. You'll begin by reviewing the Markov decision processes, Bellman equations, and dynamic programming that form the core concepts and foundation of deep reinforcement learning. Next, you'll study model-free learning followed by function approximation using neural networks and deep learning. This is followed by various deep reinforcement learning algorithms such as deep q-networks, various flavors of actor-critic methods, and other policy-based methods. You'll also look at exploration vs exploitation dilemma, a key consideration in reinforcement learning algorithms, along with Monte Carlo tree search (MCTS), which played a key role in the success of AlphaGo. The final chapters conclude with deep reinforcement learning implementation using popular deep learning frameworks such as TensorFlow and PyTorch. In the end, you'll understand deep reinforcement learning along with deep q networks and policy gradient models implementation with TensorFlow, PyTorch, and Open AI Gym. What You'll Learn Examine deep reinforcement learning Implement deep learning algorithms using OpenAI’s Gym environment Code your own game playing agents for Atari using actor-critic algorithms Apply best practices for model building and algorithm training Who This Book Is For Machine learning developers and architects who want to stay ahead of the curve in the field of AI and deep learning.


Detail About Deep Reinforcement Learning with Python PDF

  • Author : Nimish Sanghi
  • Publisher : Apress
  • Genre : Computers
  • Total Pages : 490 pages
  • ISBN : 9781484268087
  • PDF File Size : 29,8 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python
  • Publisher : Apress
  • File Size : 41,7 Mb
  • Release Date : 12 June 2021
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Deep reinforcement learning is a fast-growing discipline that is making a significant impact in fields of autonomous vehicles, robotics, healthcare, finance, and many more. This book covers deep reinforcement learning

Foundations of Deep Reinforcement Learning

Foundations of Deep Reinforcement Learning
  • Publisher : Addison-Wesley Professional
  • File Size : 29,7 Mb
  • Release Date : 20 November 2019
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The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve

Hands-On Reinforcement Learning with Python

Hands-On Reinforcement Learning with Python
  • Publisher : Packt Publishing Ltd
  • File Size : 39,7 Mb
  • Release Date : 28 June 2018
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A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python Key Features Your entry point into the world of artificial intelligence using the power of Python

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python
  • Publisher : Packt Publishing Ltd
  • File Size : 48,7 Mb
  • Release Date : 30 September 2020
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An example-rich guide for beginners to start their reinforcement and deep reinforcement learning journey with state-of-the-art distinct algorithms Key FeaturesCovers a vast spectrum of basic-to-advanced RL algorithms with mathematical explanations

Mastering Reinforcement Learning with Python

Mastering Reinforcement Learning with Python
  • Publisher : Packt Publishing Ltd
  • File Size : 27,8 Mb
  • Release Date : 18 December 2020
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Get hands-on experience in creating state-of-the-art reinforcement learning agents using TensorFlow and RLlib to solve complex real-world business and industry problems with the help of expert tips and best practices

Deep Reinforcement Learning in Action

Deep Reinforcement Learning in Action
  • Publisher : Manning Publications
  • File Size : 49,8 Mb
  • Release Date : 28 April 2020
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Summary Humans learn best from feedback—we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences. This reinforcement process can be applied

Grokking Deep Reinforcement Learning

Grokking Deep Reinforcement Learning
  • Publisher : Manning Publications
  • File Size : 31,8 Mb
  • Release Date : 10 November 2020
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Grokking Deep Reinforcement Learning uses engaging exercises to teach you how to build deep learning systems. This book combines annotated Python code with intuitive explanations to explore DRL techniques. You’

Applied Reinforcement Learning with Python

Applied Reinforcement Learning with Python
  • Publisher : Apress
  • File Size : 31,8 Mb
  • Release Date : 23 August 2019
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Delve into the world of reinforcement learning algorithms and apply them to different use-cases via Python. This book covers important topics such as policy gradients and Q learning, and utilizes

Python Reinforcement Learning Projects

Python Reinforcement Learning Projects
  • Publisher : Packt Publishing Ltd
  • File Size : 53,5 Mb
  • Release Date : 29 September 2018
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Implement state-of-the-art deep reinforcement learning algorithms using Python and its powerful libraries Key FeaturesImplement Q-learning and Markov models with Python and OpenAIExplore the power of TensorFlow to build self-learning modelsEight

Deep Reinforcement Learning Hands-On

Deep Reinforcement Learning Hands-On
  • Publisher : Packt Publishing Ltd
  • File Size : 23,6 Mb
  • Release Date : 21 June 2018
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This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems. Key Features Explore deep reinforcement learning (RL), from the first principles to