<ul><li>Supervised learning, specifically regression, involves using past data to predict continuous outcomes, like house prices based on factors such as size and location.</li><li>Regression algorithms learn the relationship between input features and continuous outputs, with types like linear regression handling linear relationships and more complex algorithms dealing with non-linear patterns.</li><li>Regression is significant in making predictions about the future across fields like finance, healthcare, and marketing, offering valuable insights for decision-making and outcome improvement.</li><li>Applications of regression span various fields such as finance, healthcare, marketing, environmental science, and engineering, empowering automation, efficiency, and new insights from data.</li></ul>

Predicting the Future: An Introduction to Supervised Learning: Regression

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