In this segment, we will implement deep Q-learning with a deep learning model built using the Keras deep learning library as the function approximator.
We will start off this segment with a gentle introduction as to how to use the Gym module and then move on to understanding what Q-learning is, and finally, implement the deep Q-learning. We will be using the CartPole environment from OpenAI Gym.
To follow along, refer to the Jupyter Notebook code file for the deep Q-learning section at https://github.com/PacktPublishing/Python-Deep-Learning-Projects/blob/master/Chapter%2015/DQN.ipynb.
