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Deep Reinforcement Learning (RL) Using Python

In this tutorial series, we are going through every step of building an expert Reinforcement Learning (RL) agent that is capable of playing games.

This series is divided into three parts:

  • Part 1: Designing and Building the Game Environment. In this part we will build a game environment and customize it to make the RL agent able to train on it.

  • Part 2: Build and Train the Deep Q Neural Network (DQN). In this part, we define and build the different layers of DQN and train it.

  • Part 3: Test and Play the Game.

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