# Introduction to the Genetic Algorithm

Learn about the genetic algorithm and its benefits in hyperparameter optimization.

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## What is the genetic algorithm?

The **genetic algorithm** is a heuristic search algorithm that is inspired by Charles Darwnin’s theory of natural evolution. This algorithm reflects the process of natural selection, where the fittest individuals are selected for reproduction to produce the offspring of the next generation. The same idea is also implemented for hyperparameter optimization to find the values of different hyperparameters that can produce the best-performing ML model.

Genetic algorithms are widely used for solving optimization problems such as:

Finding the optimal configuration of parameters or variables in engineering design

Optimizing financial portfolios

Aligning sequences, predicting protein structures, and selecting optimal genes in bioinformatics

Note:Genetic algorithms are a subset of a much larger branch of computation known asevolutionary computation.

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