Descent methods and line search: Quadratic interpolation

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Covers the Newton method for finding zeros of functions using data interpolation.

Covers the derivation of the equation of motion, interpolation, Newton's equation, and energy conservation in finite element modeling.

Introduces the basics of finite element modeling for dynamics and discusses the Newmark method for time integration.

Explores error analysis and limitations in interpolation on evenly distributed nodes.

Covers the basics of Newton interpolation and interpolation polynomials using Lagrange and Newton methods.

Explores trigonometric interpolation for approximating periodic functions and signals using equally spaced nodes.

Introduces nonlinear equations and polynomial interpolation for curve fitting.

Introduces Lagrange interpolation for approximating data points with polynomials, discussing challenges and techniques for accurate interpolation.

Explores double descent curves and overparametrization in machine learning models, highlighting the risks and benefits.

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