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Genetic Algorithm

Data Science, Analytics and AI/ML

A genetic algorithm is an optimization and search technique inspired by natural selection, in which candidate solutions ('individuals') are represented as strings of parameters and evolved over generations through selection, crossover, and mutation. It is used by computer scientists, engineers, and data scientists to find good approximate solutions to complex optimization problems, such as scheduling, design optimization, and machine learning hyperparameter tuning, where traditional analytical methods are impractical. It is a subfield of evolutionary computation within artificial intelligence.

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