Description
This course covers the working Principle of Genetics Algorithms and its various components like Natural Selection, Crossover or Recombination, Mutation and Elitism in a a very simplified way.
GA are inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on biologically inspired operators such as mutation, crossover and selection.
Who this course is for:
- Students taking Genetics Algorithm or Machine Learning or Artificial Intelligence Course
- Machine Learning Enthusiast
- Students preparing for placement tests and interviews
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