IT & Software

Genetic Algorithm for Machine Learning

Simplified Way to Learn

What you will learn

  • Working Principle of Genetics Algorithms
  • Natural Selection
  • Implementation of Natural Selection through Roulette Wheel
  • Crossover or Recombination
  • Concept of Probability of Crossover and Its usage in generation of Population
  • Mutation
  • Concept of Probability of Mutation and Its usage in generation of new features
  • Concept and Implementation of Elitism

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
- Genetic Algorithm for Machine Learning
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  • Udemy teacher
  • English
  • 0
  • 1350
  • 2022-03-17