Optimization refers to the task of minimizing/maximizing an objective function f(x) parameterized by x. In machine/deep learning terminology, it's the task of minimizing the cost/loss function J(w) parameterized by the model's parameters $w \in \mathbb{R}^d$. Optimization algorithms (in case of minimization) have one of the following goals:
Find the global minimum of the objective function. This is feasible if the objective function is convex, i.e. any local minimum is a global minimum.

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