Reinforcement Learning

Reinforcement learning is a type of machine learning where an agent learns to make decisions in an environment to maximize a cumulative reward. It involves the agent taking actions, receiving feedback in the form of rewards or penalties, and adjusting its strategy to improve its performance over time. Unlike supervised learning, it doesn't rely on labeled data but rather learns through trial and error.

Visit the following resources to learn more:

• @course@Deep Reinforcement Learning Course by HuggingFace
• @article@What is reinforcement learning?
• @article@Resources to Learn Reinforcement Learning
• @video@Reinforcement Learning in 3 Hours | Full Course using Python