Deep Reinforcement Learning introduces deep neural networks to solve Reinforcement Learning problems — hence the name “deep”.
For instance, in the next unit, we’ll learn about two value-based algorithms: Q-Learning (classic Reinforcement Learning) and then Deep Q-Learning.
You’ll see the difference is that in the first approach, we use a traditional algorithm to create a Q table that helps us find what action to take for each state.
In the second approach, we will use a Neural Network (to approximate the Q value).
If you are not familiar with Deep Learning you definitely should watch the FastAI Practical Deep Learning for Coders (Free).