This infographic explains machine learning as methods that allow systems to learn patterns and tasks without explicit programming, enabling predictive analytics. Supervised learning uses known inputs and outputs to train models, such as linear regression, for predicting outcomes or classifying records. Unsupervised learning finds hidden patterns, clusters, or correlations without labeled data, while reinforcement learning teaches agents to maximize rewards in dynamic environments like gaming or self-driving. A detailed example of supervised learning shows how linear regression minimizes squared errors to fit data trends, with algorithms computing estimators to build predictive models.

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