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Regression Algorithms

Regression algorithms are a class of supervised machine learning techniques used to predict continuous numerical values based on input features. They model the relationship between dependent and independent variables by fitting a mathematical function to observed data, enabling predictions and trend analysis. Common applications include forecasting sales, estimating house prices, and analyzing trends in time-series data.

Also known as: Regression Models, Regression Analysis, Predictive Regression, Linear Regression, Regressors
🧊Why learn Regression Algorithms?

Developers should learn regression algorithms when building predictive models for quantitative outcomes, such as in finance for stock price prediction, in healthcare for patient risk scoring, or in e-commerce for demand forecasting. They are essential for tasks requiring numerical predictions and understanding variable relationships, often serving as a foundation for more complex machine learning workflows.

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