09. Exercise Reinforcement Learning

In this exercise, we'll apply our skills to build a Reinforcement Learning model. We'll focus on using this approach to train an agent that learns to make decisions by interacting with its environment and receiving rewards or penalties. Throughout the process, we'll explore key concepts like states, actions, and rewards, and implement algorithms to optimize the agent's behavior. By the end, we will build a trading algorithm based on this model.