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Deep Reinforcement Learning

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Cover of 'Deep Reinforcement Learning'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Reinforcement Learning
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    Chapter 2 Mathematical and Algorithmic Understanding of Reinforcement Learning
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    Chapter 3 Coding the Environment and MDP Solution
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    Chapter 4 Temporal Difference Learning, SARSA, and Q-Learning
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    Chapter 5 Q-Learning in Code
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    Chapter 6 Introduction to Deep Learning
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    Chapter 7 Implementation Resources
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    Chapter 8 Deep Q Network (DQN), Double DQN, and Dueling DQN
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    Chapter 9 Double DQN in Code
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    Chapter 10 Policy-Based Reinforcement Learning Approaches
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    Chapter 11 Actor-Critic Models and the A3C
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    Chapter 12 A3C in Code
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    Chapter 13 Deterministic Policy Gradient and the DDPG
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    Chapter 14 DDPG in Code
Attention for Chapter 2: Mathematical and Algorithmic Understanding of Reinforcement Learning
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