We are delving into deep reinforcement learning.

We learn by interacting with the environment, and the rewards and punishments we receive determine our future behavior. Deep reinforcement learning brings this natural process into artificial intelligence and involves analyzing results to identify the most effective ways to move forward. Agents of deep reinforcement learning can contribute to the success of marketing campaigns, predict stock growth, and defeat grandmasters in Go and chess. Let's learn to create deep learning systems through engaging exercises, accompanied by Python code with detailed comments and clear explanations. You will see how algorithms work and learn to create your own deep reinforcement learning agents using evaluative feedback.