Genetic algorithms, a subset of evolutionary algorithms inspired by the principles of natural selection and genetics, have emerged as a powerful tool in the realm of machine learning optimization. These algorithms mimic the process of natural selection by iteratively generating a population of potential solutions and evolving them over successive generations to arrive at an optimal or near-optimal solution to a given problem.
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