Lectures related to Muller's method

Root Finding Methods: Bisection and Secant Techniques

Covers root-finding methods, focusing on the bisection and secant techniques, their implementations, and comparisons of their convergence rates.

Iterative Methods for Nonlinear Equations

Explores iterative methods for solving nonlinear equations, discussing convergence properties and implementation details.

Root Finding Methods: Secant, Newton, and Fixed Point Iteration

Covers numerical methods for finding roots, including secant, Newton, and fixed point iteration techniques.

Taylor Series and Secant Method: Numerical Analysis Techniques

Discusses the Taylor series and secant method, focusing on their applications in numerical analysis and root-finding techniques.

Numerical Methods: Iterative Techniques

Covers open methods, Newton-Raphson, and secant method for iterative solutions in numerical methods.

Coordinate Descent: Efficient Optimization Techniques

Covers coordinate descent, a method for optimizing functions by updating one coordinate at a time.

Root Finding Methods: Secant and Newton's Methods

Covers numerical methods for root finding, focusing on the secant and Newton's methods.

Numerical Analysis: Newton's Method

Explores Newton's method for finding roots of nonlinear equations and its interpretation as a second-order method.

Numerical Methods: Stopping Criteria, SciPy, and Matplotlib

Discusses numerical methods, focusing on stopping criteria, SciPy for optimization, and data visualization with Matplotlib.

Newton's Method: Convergence and Applications

Covers the convergence of Newton's method and its applications in numerical analysis.

Quasi-Newton Methods

Introduces Quasi-Newton methods for optimization, explaining their advantages over traditional approaches like Gradient Descent and Newton's Method.

Coppersmith's Method: Small Roots of Polynomials Mod N

Covers Coppersmith's method for finding small roots of polynomials modulo N efficiently.

Scientific Computing with SciPy Constants and Curve Fitting

Covers SciPy constants, curve fitting, and zero finding methods for scientific computing.

Fixed Point Theorem: Convergence of Newton's Method

Covers the fixed point theorem and the convergence of Newton's method, emphasizing the importance of function choice and derivative behavior for successful iteration.

Numerical Methods in Chemistry

Covers the implementation of numerical methods in MATLAB for solving chemical problems.