01 · Understand the idea
In simple words
Regression predicts a number rather than a category. For example, a toy model might estimate a plant’s height from its age. Linear regression uses a line or a weighted combination of features. It describes a relationship in data, but a relationship alone does not prove that one thing causes another.
Two useful terms
Prediction: the estimated output. Residual: the difference between the observed and predicted value.
Build your understanding
Linear regression models a numeric target as a weighted combination of features plus an intercept. It is a useful baseline when relationships are approximately linear. A fitted line describes the training data; it does not establish causation or guarantee sensible extrapolation.
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