Continuous Optimization for Data ScienceContinuous Optimization for Data Science The text is divided into three main parts: unconstrained optimization, constrained optimization, and linear programming. The first part addresses unconstrained optimization in single variable and multivariable functions, introducing key algorithms such as steepest descent, Newton, and quasi Newton methods. The second part focuses on constrained optimization, starting with linear equality constraints and