1. Unconstrained Optimization Methods (Used when there are no explicit constraints on variables) Gradient-Based Methods Second-Order Methods Heuristic & Meta-Heuristic Methods Bayesian Optimization 2. Constrained Optimization Methods (Used when optimization involves constraints on variables) Convex Optimization Methods Augmented Lagrangian Methods Penalty Methods Sequential Quadratic Programming (SQP) Interior-Point Methods Constraint-Specific Heuristic Approaches Here are the Wikipedia…… Continue reading Major optimization techniques in Data Science categorized by constrained vs. unconstrained scenarios – Part 1