What are the different types of Machine Learning? Explain Supervised, Unsupervised, and Reinforcement Learning with examples.

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The three main types of Machine Learning are categorized by the kind of supervision (labels) the model receives. Supervised Learning — model learns from labeled data (input → known output). Example: predicting house prices (regression), classifying emails as spam (classification). Unsupervised Learning — model learns from unlabeled data , finding structure on its own. Example: customer segmentation (K-Means), dimensionality reduction (PCA). Reinforcement Learning — an agent learns by interacting with an environment , receiving rewards for good actions. Example: game-playing AIs (AlphaGo), robotic control, RLHF for fine-tuning LLMs. Modern variants: Semi-Supervised (some labels) and Self-Supervised (labels derived from data itself) are the foundation of modern LLMs. Don't just list types — give one crisp example per type and the type of label (or lack of it). Bonus points for mentioning Semi-Supervised and Self-Supervised as the modern variants powering LLM pretraining.