Gaussian Elimination is a classical and widely used numerical method for solving systems of linear equations.

Interpolation is the process of approximating the value of a function at a given point using known values at nearby points.

Runge-Kutta Methods are a family of numerical methods commonly used to solve ordinary differential equations.

The primary goal of numerical analysis is to develop efficient algorithms for solving mathematical problems that cannot be solved analytically.

Finite Difference Methods are a widely used approach for solving partial differential equations numerically.

Numerical Error Analysis is the study of the accuracy and convergence of numerical methods.

The Trapezoidal Rule is a widely used numerical method for approximating integrals.

Dimensionality Reduction is the process of reducing the dimensionality of a dataset while preserving important information.

Gradient Descent is a widely used approach for solving optimization problems numerically.

Mathematical Modeling is the study of mathematical models and their applications to real-world problems.

Newton's Method is a widely used numerical method for solving nonlinear equations.

Numerical Solution of Differential Equations is the process of approximating the solution of a differential equation using a series of discrete values.

Power Iteration is a widely used approach for solving eigenvalue problems numerically.

Computational Complexity is the study of the behavior of mathematical algorithms as the input size increases.

Newton's Method is a widely used numerical method for solving systems of nonlinear equations.