Numerical Computing and Stability Questions

Focuses on numerical computing concepts and stable computation practices used across quantitative, scientific, and machine learning workloads. Topics include floating point precision and rounding errors, underflow and overflow, conditioning and ill posed problems, numerically stable matrix factorizations and solvers, gradient scaling and clipping in iterative optimization, mixed precision considerations, and diagnostics for identifying numerical issues.