<ul data-eligibleForWebStory="true"><li>Artificial Intelligence learns from data through supervised, unsupervised, and reinforcement learning methods.</li><li>Supervised learning involves labeled examples where the AI is taught using input and correct answers, like teaching an AI to recognize cats from images.</li><li>Unsupervised learning works without labels, requiring the AI to find patterns and organize data on its own, e.g., grouping similar images.</li><li>Reinforcement learning is trial and error learning with feedback, where the AI learns through actions and resulting rewards or punishments, such as a robot learning to walk.</li><li>Understanding these learning approaches can make AI more relatable and less mysterious.</li></ul>

Supervised vs Unsupervised vs Reinforcement Learning — Explained Simply

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