Genetic Algorithm for Machine Learning

Simplified Way to Learn

4.30 (49 reviews)
Udemy
platform
English
language
Data Science
category
instructor
Genetic Algorithm for Machine Learning
2,809
students
1.5 hours
content
Jan 2021
last update
FREE
regular price

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

Why take this course?

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.

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Related Topics

3726066
udemy ID
12/24/2020
course created date
1/29/2021
course indexed date
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