Linear Regression
In plain terms
A model fitting a straight-line relationship to predict values.
Going deeper
Linear regression models a continuous output as a weighted sum of inputs, finding the best-fitting line. It predicts numbers, not categories.
Under the hood
Assumes linearity and independence; interpretable coefficients, foundational to statistics and ML.
Examples
Price prediction, trend forecasting, statistics, baseline regression.
Think of it like...
Like drawing the best straight line through scattered points to predict trends.