Conjugate Gradient Method Explained Visually (Solving Quadratic Optimization and Linear Systems)

In this video, we break down the Conjugate Gradient (CG) Method from scratch — one of the most powerful iterative algorithms for solving quadratic optimization problems and linear systems Ax = b. Topics covered: • How quadratic optimization reduces to a linear system • Step-by-step derivation of all update equations • How to compute the optimal step size (α) and coefficient (β) • Why conjugate directions converge faster than steepest descent • Visual walkthrough of CG iterations on a 2D example 📧 Contact: chenxy346@gmail.com 🌐 Homepage: https://xinychen.github.io #maths #linearalgebra #machinelearning #scientificcomputing #algorithm #optimization #mathematics