Assignments in Unconstrained Optimization course covering 1st half of Nocedal and Wright textbook. Topics covered are in the subject of numerical algorithms for convex optimization. The implementation is in matlab code using different matlab optimization packages and functions such as quadprog and fmincon. The reports are written in LaTex.
The first assignment covers least squares data fitting techniques, polynomial fitting, basis expansion, and how it relates to overfitting. Nonlinear optimization algorithms fo unconstrained optimization are also covered: Newton Method, Quasi-Newton, BFGS, LMarquadt, Gauss-Newton and such.