Module
Linear Models for Regression and Classification
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About
Linear regression (ordinary least squares), logistic regression, feature maps / polynomial features, and closed-form vs. iterative solutions.
Goal
Derive and implement OLS (normal equations and GD); fit logistic regression with GD; use polynomial/basis expansions; evaluate with appropriate metrics (MSE, accuracy, log-loss).
Prerequisites
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