How does NumPy handle large-scale numerical stability issues?

NumPy relies on numerically stable algorithms from BLAS/LAPACK.

Operations like matrix inversion, decomposition, and solving linear systems use numerically stable algorithms to reduce floating-point error propagation. Techniques like pivoting, normalization, and reordering are used internally to improve stability.