Python Machine Learning Cookbook - Second Edition

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Optimization problems are usually so complex that it is not possible to determine a solution analytically. Complexity is determined primarily by the number of variables and constraints, which define the size of the problem, and then by the possible presence of non-linear functions. An analytical solution is only possible in the case of a few variables and extremely simple functions. In practice, to solve an optimization problem, it is necessary to resort to an iterative algorithm, that is, to a calculation program that, given a current approximation of the solution, determines, with an appropriate sequence of operations, a new approximation. Starting from an initial approximation, a succession is thus determined.