Reinforcement Learning Basics

Daniel and Chris delve into the fundamental concepts of reinforcement learning, discussing the role of agents, policies, and rewards in training models to make decisions based on environmental feedback. They explore how neural networks fit into this feedback loop, illustrating how models can determine actions based on input data like image recognition.