Model.fit is More Complex Than it Looks

Linear regression’s closed-form solution looks simple, but computing inverse matrix is numerically dangerous. Ill-conditioned matrices, floating-point limits, and squaring the condition number in XᵀX can explode errors. Use SVD-based solvers (like model.fit), scaling, L2 regularisation, or iterative methods instead of naive matrix inversion.