Genetic algorithm

11.5 Practical Genetic Algorithms - J. Bunn

From playlist Big Data Analytics - JPL/Caltech

9.1: Genetic Algorithm: Introduction - The Nature of Code

Welcome to part 1 of a new series of videos focused on Evolutionary Computing, and more specifically, Genetic Algorithms. In this tutorial, I introduce the concept of a genetic algorithm, how it can be used to approach "search" problems and how it relates to brute force algorithms. 🎥 Next

From playlist Session 2 - Genetic Algorithms - Intelligence and Learning

9.10: Genetic Algorithm: Continuous Evolutionary System - The Nature of Code

In this video, I apply the Genetic Algorithm to an "Ecosystem Simulation", a system in which models biological life more closely, where elements live and die continuously evolving over time. 💻Code : https://github.com/CodingTrain/Rainbow-Code 🎥Previous video : https://youtu.be/Zy_obitkyO

From playlist Session 2 - Genetic Algorithms - Intelligence and Learning

9.2: Genetic Algorithm: How it works - The Nature of Code

In part 2 of this genetic algorithm series, I explain how the concepts behind Darwinian Natural Selection are applied to a computational evolutionary algorithm. 🎥 Previous video: https://youtu.be/9zfeTw-uFCw?list=RxTfc4JLYKs&list=PLRqwX-V7Uu6bJM3VgzjNV5YxVxUwzALHV 🎥 Next video: https://yo

From playlist Session 2 - Genetic Algorithms - Intelligence and Learning

Continuous Genetic Algorithm - Part 1

This video is about Continuous Genetic Algorithm - Part 1

From playlist Optimization

Lecture: Linear Programming and Genetic Algorithms

We consider a number of more advanced optimization algorithms that include the genetic algorithm and linear programming for constrained optimization.

From playlist Beginning Scientific Computing

Binary Genetic Algorithm - Part 1: Introduction

This video is about Binary Genetic Algorithm - Part 1: Introduction

From playlist Optimization

9.9: Genetic Algorithm: Interactive Selection - The Nature of Code

In this genetic algorithms video, I discuss a technique known as "interactive selection" where the algorithm's fitness function is calculated based on user / viewer interaction. 💻Code : https://github.com/CodingTrain/Rainbow-Code 🎥Previous video : https://youtu.be/ETphJASzYes 🎥Next video

From playlist Session 2 - Genetic Algorithms - Intelligence and Learning

Binary Genetic Algorithm - Part 2: Working Principle and Coding/Encoding Processes

This video is about Binary Genetic Algorithm - Part 2: Working Principle and Coding/Encoding Processes

From playlist Optimization

Data Science - Part XIV - Genetic Algorithms

For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview on biological evolution and genetic algorithms in a machine learning context. W

From playlist Data Science

Machine Learning Control: Genetic Algorithms

This lecture provides an overview of genetic algorithms, which can be used to tune the parameters of a control law. Machine Learning Control T. Duriez, S. L. Brunton, and B. R. Noack https://www.springer.com/us/book/9783319406237 Closed-Loop Turbulence Control: Progress and Challenges

From playlist Data-Driven Control with Machine Learning

Machine Learning Control: Genetic Programming

This lecture explores the use of genetic programming to simultaneously optimize the structure and parameters of an effective control law. Machine Learning Control T. Duriez, S. L. Brunton, and B. R. Noack https://www.springer.com/us/book/9783319406237 Closed-Loop Turbulence Control: Pr

From playlist Data-Driven Control with Machine Learning

11.1: Introduction to Neuroevolution - The Nature of Code

Welcome to a new topic in the Nature of Code series: Neuroevolution! 🎥 Next Video: https://youtu.be/kCx2DElEpP8 🔗 Toy-Neural-Network-JS: https://github.com/CodingTrain/Toy-Neural-Network-JS 🔗 Nature of Code: http://natureofcode.com/ 🎥 My Neural Networks series: https://www.youtube.com/p

From playlist 11: Neuroevolution - The Nature of Code

Machine Learning Control: Tuning a PID Controller with Genetic Algorithms

This lecture shows how to use genetic algorithms to tune the parameters of a PID controller. Tuning a PID controller with genetic algorithms is not generally recommended, but is used to demonstrate evolutionary control algorithms. Machine Learning Control T. Duriez, S. L. Brunton, and B

From playlist Data-Driven Control with Machine Learning

Live Stream #52: Genetic Algorithms

This entire Live Stream is dedicated to Genetic Algorithms! I cover what defines a genetic algorithm and how it relates to brute force algorithms. I also use a genetic algorithm to solve the Shakespeare Monkey problem and other programming challenges. 16:45 - Presenting today's topics 35:

From playlist Live Stream Archive