Explore different Optimization Techniques.
- Work 1: Find the minimum of convex functions [1-D].
- Work 2: Find the minimum of a function [2-D]. Methods used: Steepest Descent and Newton
- Work 3: Find the minimum of a function [2-D]. Methods used: Levenberg-Marquardt, Conj. Gradient and Quasi-Newton
- Work 4: Find the minimum of a function, with constraints [2-D].
- Project: Genetic Algorithm for function approach [2-D].
As of the completion of the project, it will NOT be maintained. By no means should it ever be considered stable or safe to use, as it may contain incomplete parts, critical bugs and security vulnerabilities.
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