<ul><li>Machine learning is a transformative technology that consists of different paradigms or fundamental approaches—supervised learning, unsupervised learning, and reinforcement learning.</li><li>Supervised learning involves learning with labeled examples, making it useful for tasks like image classification, spam detection, and medical diagnosis.</li><li>Unsupervised learning explores data without labels to discover hidden patterns, useful in areas like customer segmentation and anomaly detection.</li><li>Reinforcement learning involves learning through trial and error, making it suitable for applications like robotics control, game playing, and personalized recommendations.</li></ul>

Decoding the World: An Introduction to Machine Learning Paradigms

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