Discover how to apply genetic algorithms to solve everyday problems in this 44-minute conference talk from MLCon. Explore the practical applications of evolutionary computation as speaker Mey Beisaron demonstrates coding a genetic algorithm from scratch to generate weekly schedules and create smart diet plans. Learn about the different stages of genetic algorithms, including population generation, fitness functions, selection processes, and implementation techniques. Gain insights into constraint satisfaction and see how concepts like the "Frog Game" can be applied to optimize solutions. By the end of this talk, acquire the knowledge to leverage genetic algorithms for tackling personal challenges and enhancing daily life efficiency.
Evolution 3.0 - Solve Your Everyday Problems with Genetic Algorithms
MLCon | Machine Learning Conference via YouTube
Overview
Syllabus
Introduction
Constraint Satisfaction
Evolutionary Computation
Genetic Algorithms
Generating the Population
Fitness Function
Gap Between Classes
Clashes
Selection
Frog Game
Implementation
Summary
Taught by
MLCon | Machine Learning Conference
