Udemy - Genetic Algorithms in Python and Matlab

-BiFiSOEnglish | Size: 1.64 GBCategory: TutorialGreetings and respect to the people and groups who are willing and trying to renew the scene And of course all who supports us, we love youRequirementsBasic Math and OptimizationPython ProgrammingMATLAB ProgrammingDescriptionGenetic Algorithms (GAs) are members of a general class of optimization algorithms, known as Evolutionary Algorithms (EAs), which simulate a fictional environment based on theory of evolution to deal with various types of mathematical problem, especially those related to optimization. Also Genetic Algorithms can be categorized as a subset of Metaheuristics, which are general-purpose tools and algorithms to solve optimization and unsupervised learning problems.In this series of video tutorials, we are going to learn about Genetic Algorithms, from theory to implementation. After having a brief review of theories behind EA and GA, two main versions of genetic algorithms, namely Binary Genetic Algorithm and Real-coded Genetic Algorithm, are implemented from scratch and line-by-line, using both Python and MATLAB. This course is instructed by Dr. Mostapha Kalami Heris, who has years of practical work and active teaching in the field of computational intelligence.Components of the genetic algorithms, such as initialization, parent selection, crossover, mutation, sorting and selection, are discussed in this tutorials, and backed by practical implementation. Theoretical concepts of these operators and components can be understood very well using this practical and hands-on approach.At the end of this course, you will be fully familiar with concepts of evolutionary computation and will be able to implement genetic algorithms from scratch and also, utilize them to solve your own optimization problems.Who this course is for:Computer Science StudentsEngineering and Applied Math StudentsAnyone interested in OptimizationAnyone interested in Computational IntelligenceAnyone interested in MetaheuristicsAnyone interested in Evolutionary Computation